Ipa as a therapeutic agent, as a protective agent, and as a biomarker of disease risk

ABSTRACT

Indole-3-propionic acid as a marker and for treatment for Huntington Disease.

CROSS REFERENCE TO RELATED APPLICATION

This application is a divisional of U.S. application Ser. No.14/515,399, filed Oct. 15, 2014, which application in turn is adivisional of U.S. application Ser. No. 14/092,677 filed Nov. 27, 2013,which in turn is a divisional of U.S. application Ser. No. 13/829,773,filed Mar. 14, 2013, which claims priority from U.S. ProvisionalApplication Ser. No. 61/616,984, filed Mar. 28, 2012, the contents ofwhich are incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present disclosure relates to the use of indole-3-proprionic acid(IPA) as a therapeutic agent, as a protective agent against late onsetof cardiovascular and neurodegenerative disease, and as a biomarker fordisease and health conditions. The disclosure has particular utility inconnection with neurodegenerative diseases such as Huntington Disease(HD), Alzheimer Disease (AD), Mild Cognitive Impairment (MCI), LowerMotor Neuron Disease (MND) including but not limited to AmyotrophicLateral Sclerosis (ALS), Parkingson's Disease (PD) as well ashypertension, stroke and ischemic heart disease and head injury, andwill be described in connection with such utilities, although otherutilities are contemplated.

IPA is an indole produced in organisms such as c. Sporogenes that havethe enzyme to remove the OH from the 2 position on the propionic acidside chain of indole lactic acid an end product of tryptophan metabolismin mammalian species. It is one of several gut metabolites that affectthe plasma metabolome [12]. Other organisms such as brewers yeast alsoshow the ability to produce IPA (See below a means of producing purifiedIPA preparations using brewers yeast or similar organisms). Currentunderstanding is that IPA serves as an antioxidant whose intermediateindoxyl positive free radical, unlike such compounds as tocopherols andcarotenes has no pro oxidant intermediates [11,14,15,17] and in vitrohas been shown to suppress protein aggregation and suggested as atherapeutic for Alzheimer's Disease [13,16,18]. IPA also has been shownin culture studies to suppress other microbial species such as E. coli(Pauley et. al. Effect of Tryptophan analogs on depression of theEnchiridia Coli Tryptophan Operon by Indole 3 propionic Acid: Journal ofBacteriology 219-226 (1978). We have shown that in plasma IPA isstrongly bound to plasma proteins both albumin and immunoglobulins withnormal plasma levels of ca. 200 ng/ml and free levels of ca. 0.1 ng/ml.The loading capacity of plasma for IPA is approximately 10 ug/ml beforesignificant additional loading shows linearity of free material withadded material. In plasma loading studies IPA replaces other indolessuch as 3 hydroxy kynurenine and 3 hydroxy anthranillic acid which arethought to have possible deleterious effects on protein. We have shownthat on free radical attack the intermediate positive ion free radicalbinds to protein as a kynuric acid moiety. The displacement of otherindoles, the strong coordinate binding to protein and the defense of theprotein against free radical attack leaving a residue that does not leadto crosslinking and denaturation are mechanisms that provide protectionand improve functionality of an organism. We have shown that IPAproduced in the gut enters the plasma and crosses the BBB and is foundin brain and CSF. Residual fecal levels are lower than plasma levels andindicate that the majority of IPA produced is transferred to plasma.Intra peritoneal injected IPA derivative such as the amide (IPAM) arerapidly converted to IPA in the plasma. We also have identified twometabolites of IPA that allow monitoring of levels in excretion samplessuch as urine which correlate with plasma and brain levels.

Many late onset illnesses of the CNS or cardiovascular system havecharacteristics of free radical damage reflected in reduction ofprotective agents such as tocopherols, ascorbate etc. and damageproducts of lipids proteins and DNA. Different approaches to controllingthis aim at different structures and processes—Antioxidants such asCoQ10 to reduce DNA damage and protect mitochondrial function, selectedlipid diets to reduce lipid oxidation, materials such as creatine toenhance energy efficiency and reduce free radical burden, ascorbate toprovide general peripheral protection. CNS disorders such as MCI, AD andHD and to a more limited extent PD and ALS also involve proteinaggregation-currently considered to be the proximal cause of neuronaldeath in Huntington's disease, Alzheimer's disease and otherneurodegenerative disorders. Specific agents to prevent damage toproteins have not been as extensively studied. These commonalties inlate onset disease lead to the concept that there is a failure ofcontrol of the biochemical system reflecting the interaction andfeedback among the genome transcriptome, proteome metabolome environmentand commensal gut microbiome. It is this failure of feedback that infact is the disease and that leads eventually to the symptoms.Consequently one looks for places in the network where genetic orenvironmental changes have created a non lethal but sub optimal level ofcontrol. These nodes or compounds can then be evaluated as therapeuticsor as risk factors that like cholesterol for instance can be modified toreset or reestablish control.

We have shown in animal models and in human studies that the individualsgenome determines the aggregate composition of the commensal gutmicrobiome and consequently the levels of I3PA produced in the gut. I3PAlevels are then to an extent an inherited characteristic and low levelsthat are present in neurodegenerative and cardiovascular diseaseconstitute an inherited characteristic that place individuals at higherrisk for these diseases. Increasing these levels by supplementationand/or by modification of the aggregate makeup of the commensal gutmicrobiome is thus and approach to reducing risk as well as atherapeutic approach to intervention when such risk has been realized inthe development of symptoms of disease.

SUMMARY OF THE DISCLOSURE

The network of biochemical interactions in an individual is determinedby the individual genome, the effect of the individuals genome on theindividuals commensal microflora and the feed back among the genome,transcriptome, proteome, metabolome, microbiome and environment. In thiscontrol network there are individual compounds and genes that constitutepotential risk factors that can be modified to improve the probabilityof not developing late onset diseases caused by non lethal but suboptimal control. A well known example is cholesterol that is bothgenetically and environmentally determined.

We have discovered that IPA levels are individual specific indicators ofrisk factor for certain diseases. More particularly, we have identifieddecreased levels of IPA in individuals suffering from neurodegenerativediseases (Huntington's Disease (HD), Presymptomatic HD, Alzheimer'sdisease (AD) and Mild Cognitive Impairment (MCI), Lower Motor NeuronDisease (LMND), Amyotropic Lateral Sclerosis (ALS), Parkinson's disease(PD)) and in hypertension stroke and individuals with ischemic heartdisease, and have also shown that IPA is decreased in ischemic heartdisease subjects undergoing mental and/or physical stress tests.

We have shown that IPA levels are not impacted over the short term bySSRI or antihypertensive drugs. Data from studies with serial samplesshow that IPA is a highly specific individual specific characteristic(FIG. 29). We have shown that IPA levels are related to the genomicmakeup of the individual through the effect of the individual's genomeon the aggregate genome of the gut microbiome and that levels are highlyconstant in an individual in the absence of intervention or possibledevelopment of certain disease states of the gut (FIG. 29). Theindividual specificity of IPA levels, the genomic relationship, theprevalence of low levels in numerous disorders and particularly theprogression of sequentially lower levels in normal individuals,individuals with MCI and individuals with AD indicate that it is agenetically determined risk factor for the development such late onsetdisorders as neurodegenerative diseases and hypertension and ischemicheart disease. The reason for low IPA levels can thus be both geneticand environmental including different diet and stress situations of anindividual. Since it is inherently easier to influence the aggregategenome of the gut microbiome than the genetic make up of an individual,we propose therapeutic intervention to reduce risk using IPA as a markerby focusing on directly increasing IPA levels or modification of the gutto increase IPA levels. Since IPA is related to the composition of thegut microbiome we developed techniques to show that genetic modificationof mice creates a unique associated microbiome indicating that inherentlevels of IPA are dependent to on the genetic modification. We also haveshown that the microbiome reflected in the foot print of the organismsin fecal material is an individual specific characteristic of humansubjects.

Thus, we have found that low IPA like high Cholesterol is innately aninherited risk factor for disease that should be monitored and adjustedby therapeutic supplementation or gut microbiome modification in thepopulation with low IPA levels as a whole.

We also have determined that in certain traumas such as stroke whichsignificantly reduces IPA levels in CSF and plasma, or potential traumassuch as military combat or high intensity contact sports IPAsupplementation will provide a protective effect against protein andoxidative damage occurring as sequelae.

We also discovered that IPA level monitoring advantageously may be usedin drug development. Trials of a therapeutic agent are expensive at allphases from initial animal studies to phase 1, 2 and 3 trials in humans.In animal trials minimizing the number of animal cohorts will reduceexpenses considerably which can be achieved by using new technologieswith micro techniques of analysis and by analysis of total patterns ofmetabolomic interactions that reduce the need to sacrifice animals fordose finding and pharmacokinetic studies.

In phase 1 safety and tolerability and dose finding similar processescan be used to develop baseline individual biochemical patterns ofdifferences in metabolism of the therapeutic agent and its metabolitesand overall biochemical patterns and network relationships. Sucharchived data from phase 1 studies provides the baseline for possiblespecification of outcome or possible contra indication

In phase 2 trials use of non invasive biomarkers can be used for morecomplete assessment of compliance and continuation of the acquisition ofthe archived data will provide again insight into specification andadverse effects and indications of adjunctive therapeutics or processesreverse such affects.

In phase 3 assessing compliance with non invasive biomarkers will allowthe better assessment of therapeutic outcome and verify or validate anybiomarkers or biochemical anomalies that are contraindicated in the useof a therapeutic agent.

A common persistent problem in assessing body burden in animal trials ofa therapeutic agent and in assessing compliance in human trials isproviding means of non invasive monitoring of levels of the therapeuticor effects of an intervention. A second potential problem is indeveloping an initial set of multiple metabolites and changes in theoverall metabolomic network that may have individual specific or groupdeleterious effects.

The process of developing markers of therapeutic intervention formonitoring and potential deleterious markers involves an initial step ofloading a test animal or human individual with the compound of interestand subsequently performing serial global metabolomic profiling tests ofurine saliva and plasma and feces (or with mice of serial urine plasmafeces and subsequently brain, cord and other organs. The profiles areanalyzed by total pattern matching not only to determine traditionalpharmaco kinetics but also to detect and identify any metabolites of thecompound and any changes in the overall self similarity and endogenouscompounds or compound relationships. Typically metabolomic profiles aremeasured for coordinately bound compounds yielding ca 1500-2000responses. Protocols for analyzing unknown compounds of statisticalsignificance have been developed. Following the use of global metabolicprofiling according to the teaching above rapid targeted methods aredeveloped to: (1) allow rapid minimally or non invasive monitoring orcompounds of significance in drug trials, and (2) allow population widemonitoring of compounds related to risk factors of disease for potentialmodification and risk reduction.

As an example we have developed a system for assessing the levels of IPAin both animal and human samples of spot urine 5-10 ul and or fingerstick whole blood 20-50 ul. Monitoring in urine is possible because ofthe discovery of two electro active metabolites of IPA in dosing studiesin R6/2 mice (See FIG. 30) from which we isolated and determined twopeaks (FIG. 25), as will be discussed below. Using coulometric sensortechnology we are able to determine the total coulombs and number ofelectrons involved in oxidation of the materials as 1. This allowsdirect determination of the moles of material excreted and assessment ofthe body burden of the material. The levels of these peaks correlatewith levels of plasma in the mice. The same metabolites occur in humansubjects and correlate with plasma IPA. The assay can be done on liquidspot urine or more conveniently on urine dried on filter papernormalizing the values of the metabolites to creatinine or to the totalintegrated electroactive species in the sample. The filter paperapproach can be generalized to any metabolites of any compound that maybe studied.

The advantage of the discovery of these metabolites in animal studies isthat it allows the monitoring of a test cohort without any sacrifice ofthe animals in the initial steps of determining dose loading and thefollowing steps of assessing actual drug levels during survival andbehavioral studies.

In human trials urinary measurements and/or use of finger stick bloodsamples either alone or taken to filter paper matrix offer a means ofmonitoring both compliance and adsorption of various formulations. Suchmethods also offer a convenient protocol for acquisition of samples forrisk assessment of levels of compounds such as IPA by an individual inthe home environment to reduce the costs of monitoring on a populationwide basis.

As well as providing a system for monitoring in direct supplementationor therapeutic use of a compound this protocol also allows tracking ofprotocols to modify the gut microbiome directed at increasing the levelsof potentially beneficial compounds such as IPA or decreasing the levelsof potentially harmful compounds such as cresoles or benzoates.

Further this rapid targeted protocol allows the development of aprocedure for evaluating the levels of IPA in prior archived profilesand sample sets across a range of neurological diseases and studieswhere it had previously not been structurally identified prior to ourwork in concentrating and identifying the peak with a concentration andparallel LCEC/LCMS protocol.

The following is a protocol that we have developed suitable forevaluation of IPA by an individually acquired sample to enabledetermination of IPA levels; to determine if increased levels would putthe individual into a lower risk category and to supply and monitorstrategies for increasing IPA levels by supplementation, gut microfloramodification or dietary modification.

The kit contains 4 strips of high absorbent filter paper labeled AMfasting urine, AM fasting Blood, PM non fasting urine, PM non fastingblood in individual color coded accession numbered zip lock bags in aninsulated shipping kit with a small ice pack. In the morning theindividual takes a mid stream urine sample to the filter paper labeledAM fasting urine and a finger stick blood sample to the filter paperlabeled AM fasting blood, placing the samples in the appropriate ziplock bags in the shipping kit. In the evening the individual takes a midstream urine sample to the filter paper labeled PM non fasting Urine anda finger stick sample to the filter paper labeled PM non fasting bloodplacing the samples in the shipping kit. The shipping kit is then mailedto the laboratory.

Urinary levels of IPA metabolites and blood levels of IPA are determinedfrom the samples provided and a report based on the sample accessionnumber is sent to the mailing address. The report identifies thequintile of the individuals IPA level and the relative risk associatedwith that level. If indicated the report will suggest appropriatesupplements and or modifications to raise IPA levels. These may includedirect ingestion of IPA at suggested specified levels in preparations ofpurified free IPA, IPA bound to protein or bound to inert materials suchFroximum (inorganic ash supplement), or activated charcoal, and/orsuggested modifications of diet. The effectiveness of the supplements ormodifications will be evaluated using a second test kit after a periodof 4-8 weeks.

In certain instances IPA levels may be greater than the mean controllevels by over 3 standard deviations. In prior work we have seen suchlevels in cases of gut disorders such as Celiac disease, Diverticulitis,or leaky gut syndrome. High IPA as such is not a diagnostic for thesedisorders but is an indicator that they or other gut microbiomeabnormalities may be present. In cases where such levels are found nosupplementation would be suggested but rather a suggestion of possiblefollow up with medical professionals.

Our animal model and human studies indicate that IPA is best adsorbedthrough the gut and optimally IPA preparations should reach the gutbefore becoming available. This can be accomplished by encapsulationand/or by providing the IPA in a form coordinately bound to protein orbound coordinately to an inorganic inert matrix. The coordinately boundforms of which are not easily released by HCl at concentrations in thestomach.

Consider Huntington Disease (HD) as an example. (HD) is a debilitatingneurodegenerative disease characterized by gradual onset motordysfunction, dementia, weight loss and emotional disturbances. HD isinherited in an autosomal dominant fashion and occurs in approximately5-10 cases per 100,000 individuals [1,2]. It manifests itself in allraces and ethnic groups [3]. Currently, in North America, approximately30,000 individuals are affected by HD and it is likely that close to150,000 others may develop the condition. Although the age of onsetvaries from infancy to the early eighties, the average age of onset isin the late thirties. The disease progresses over the course of severalyears in affected individuals, eventually preventing these individualsfrom functioning independently.

Occasionally especially when the onset of symptoms occurs before age 20,choreic movements are less prominent; instead bradykinesia and dystoniapredominate. As the disorder progresses, the involuntary movementsbecome more severe, dysarthria and dysphagia develop, and balance isimpaired. The cognitive disorder manifests first as slowness of mentalprocessing and difficulty in organizing complex tasks. Memory isimpaired, but affected persons rarely lose their memory of family,friends, and the immediate situation. Such persons often becomeirritable, anxious, and depressed. Less frequently, paranoia anddelusional states are manifest. The outcome of HD is invariably fatal;over a course of 15-30 years, the affected person becomes totallydisabled and unable to communicate, requiring full-time care; deathensues from the complications of immobility.

Unfortunately there is currently no therapy proven to delay onset or toslow progression of the disease, although efforts are being made todevelop more effective treatments. The vast majority of currenttreatment options target managing symptoms related to the disease andassisting with maximizing a patient's function [4-6].

HD patients are frequently very sensitive to side effects ofmedications. Treatment is needed for patients who are depressed,irritable, paranoid, excessively anxious, or psychotic. Depression canbe treated effectively with standard antidepressant drugs with thecaveat that drugs with substantial anticholinergic profiles canexacerbate chorea. There is also a body of anecdotal evidence that theSSRI Sertraline can cause a range of undesirable side effectsspecifically in HD. Our studies of Sertraline in depression show a dropbut not statistically significant lowering of IPA levels on 4 weeks ofSertraline therapy which is not seen in studies of IPA levels insubjects taking Citalopram or Escitalopram.

As HD progresses, psychiatric, physical and functional effects becomemore pronounced, leading to the need for increased care from familymembers and health care providers.

In 1993, the HD gene was first mapped and cloned [7]. The gene codes fora protein which contains 3144 amino acids and is called “huntingtin”. Inindividuals with HD, a trinucleotide repeat sequence (CAGn) located nearthe 5′ end of the gene is expanded beyond the normal repeat range [7]and this causes translation of an expanded polyglutamine sequence in theprotein. Normal individuals usually have between 17 and 29 CAG repeats.Individuals with HD have more than 38 of these repeats. For individualshaving more than the “normal” number of repeats, there is a relationshipbetween the number of CAG repeats and the age of disease onset, withhigher numbers of repeats leading to earlier onset of disease symptoms.The exact correlation is still being investigated.

Interestingly, in HD, only certain types of neurons are targeted by thedisease. Certain populations of neurons degenerate while other lessvulnerable populations are not affected [8]. The area most affected byneurodegeneration is the neostriatum, although research has shown thatneuronal loss occurs in many other regions of the brain as well [8].Both degenerative and proliferative changes [9, 10] in certain neuronssuggest that mutated huntingtin is the cause of compensatory anddegenerative genetic programs in a process that takes place over manyyears. The sequence of events starts with neuronal dysfunction andeventually leads to death.

Much is still unknown about the biochemical mechanisms of HD. A clearpathway from genetic mutation to neuronal dysfunction has not yet beenfully established and understood. The function of huntingtin, apredominantly cytoplasmic protein, is unknown. It is commonly expressedand it has been found to be spread throughout neurons in the brain[11-15]. Most individuals who have the disease possess both normal andmutant alleles, which, in aggregate, create functional changes in whichthe mutant huntingtin exhibits toxic effects.

It has been suggested that the proteolysis of mutant huntingtin andrelease of the toxic N-terminal fragment may play a direct role incausing the disease [16-18]. In human, animal and cellular models, thepresence of the N-terminal fragment has been shown to lead to proteinaggregation in the nucleus and cytoplasm [19-21]. It has also been shownto interfere with the normal processes of neurons. In the normal pathwayfor elimination of protein aggregates, ubiquitination assists in theremoval of these unwanted structures. However, in the case of theN-terminal fragments mentioned above, although ubiquitination occurs,the proteins still remain. It has been proposed that this phenomenon mayresult from misfolding of the protein and failed mechanisms of proteindegradation [22, 23]. Other studies of HD aggregates suggest the abilityof variant huntingtin to sequester certain proteasomal proteins [24],chaperones [25], normal huntingtin [26], and transcription factors[27-33]. Huntingtin aggregates have been observed in brain tissue fromboth patients who died as a result of having HD and those who wereat-risk but died before exhibiting symptoms of HD [21, 34-36].

There is still much discussion surrounding the exact mechanism for thedamage caused by huntingtin aggregates [37]. Most research suggests thatthe toxicity is created by mutant huntingtin or its fragments and theirinteractions with other proteins and transcription factors. Mutanthuntingtin may also trigger deleterious biochemical cascades which alterthe environment such that the relevant proteins become increasinglysusceptible to alteration by oxidative damage, apoptotic signals, energydepletion, and excitotoxic stress. All of these could potentially leadto disordered physiology which results in the death of neurons [38].

Recently, greater understanding of these causes of these biochemicalprocesses has allowed for the proposal of certain therapeuticinterventions. Some of these have been studied through the use of HDtransgenic mouse models.

There are numerous challenges inherent in the development of creatingtherapies for HD. In general, there are two goals. The first is to beable to treat patients with HD by delaying or preventing disease onsetin those who are at-risk genetically. The second goal is to developtherapies to slow the progression of the disease in those alreadyafflicted. Creating both types of therapies is challenging andtime-consuming. In general, potential therapies are first tested andfiltered through genetic mouse models of HD when preclinical datasuggests that a compound may act in a neuroprotective role. If thecompound successfully shows efficacy in mouse models, it is evaluated inphase I drug trials. Unfortunately, the majority of compounds evaluateddown this pipeline are preexisting.

Another method being utilized is the “shotgun” method where dozens ofcompounds are tested at once to see if they are able to ameliorate theneurodegeneration in HD. Although somewhat crude, this approach hashelped to increase the number of starting compounds being tested againstHD.

As one can imagine, the above process can be complex and time-consuming.Genetic animal models are costly, slow and not entirely geneticallyaccurate representations of the “human” condition of HD, as the mostcommonly used R6/2 mice typically live only 100 days. Longer lived HDmouse models such as the CAG140 significantly extend the time and costof initial animal model trials. Ideally, it would be most useful todiscover biomarkers of therapeutic response from genetically modifiedanimal models, that affect pathways, mechanisms and compounds that arecongruent in both the mouse and human, as they would help researchers todetermine the effects of a particular therapy on the animals, and thuswould provide mechanistic information about potential drug effects inhumans and an indication as to whether the drug may delay the onset ofneurodegeneration in the human as well as in the mouse model.

Additional challenges to the process arise in phase I and II trials.Although discovering tolerable dose ranges for compounds being tested inHD patients is usually a straightforward process, it may be difficult tofind quantitative “signals” which indicate whether the compound iseffective. A method which allows the measure of these “signals” wouldtherefore be of great importance, because it would justify thecontinuation of these studies in phase III trials. Without quantitativesignals/biomarkers such as these, it is difficult to justify thecontinued study of a particular compound as the symptoms of HD are quitevariable and their alteration does not necessarily correlate toamelioration of the disease itself. An example of this phenomenon isseen in the drug Haldol, which may help to lessen a patients' chorea,but may have other deleterious side effects [39]. In this example,improving the symptoms of the disease does not actually slow the diseaseprocess, which ultimately would be the most positive outcome of aparticular drug study.

Lastly, the final challenge arises in phase III clinical trials. Theconclusions from current studies in patients exhibiting symptoms of thedisease are based on changes in the TFC (total functional capacity)scores which require measuring hundreds of subjects over at least 5years to observe small changes (20% slowing) of decline. In order todetermine whether a treatment actually delays the onset of symptomsclinically, in patients with the mutation who are presymptomatic, it maytake thousands of subjects and dozens of years of follow-up to detectslight changes in the occurrence of symptom onset. As one can imagine,each of these trials requires time, financing and great effort on thepart of the clinical investigator. Thus, very few interventions can be(and are) tested. Hence, there would be a great advantage to being ableto discover both biomarkers of disease progression and biomarkers whichallow for the determination of whether the disease is being slowed in afaster, simpler and less expensive manner.

In one aspect, the present disclosure provides a method for identifyingone or more markers for Huntington Disease or other neurodegenerativediseases, or hypertension, stroke or ischemic heart disease. In anotheraspect, the present disclosure provides a method for monitoringprogression of Huntington Disease or other neurodegenerative diseases,or hypertension, stroke or ischemic heart disease and/or effectivenessof therapies for Huntington Disease or other neurodegenerative diseases,or hypertension, stroke or ischemic heart disease. In still yet anotheraspect, the present disclosure provides a method for therapeuticmonitoring and for treating Huntington Disease or otherneurodegenerative diseases, or hypertension, stroke or ischemic heartdisease, and to therapeutic agents useful for treating HuntingtonDisease or other neurodegenerative diseases, or hypertension, stroke orischemic heart disease.

In another aspect, the present disclosure provides a pharmaceuticalcomposition for treating or preventing Huntington Disease or otherneurodegenerative diseases, or hypertension, stroke or ischemic heartdisease in an animal, including a human, or for delaying or amelioratingthe effects of Huntington Disease or other neurodegenerative diseases,or hypertension, stroke or ischemic heart disease in an animal sufferingfrom same, said composition comprising indole-3-propionic acid or a saltor ester or protein complex or inorganically bound preparation thereofand a pharmaceutically acceptable carrier therefor. In a preferredembodiment, the pharmaceutically acceptable carrier comprises a food orbeverage with a specified quantity of IPA.

The present disclosure also provides a method for treating HuntingtonDisease or other neurodegenerative diseases, or hypertension, stroke orischemic heart disease in an animal in need of said treatment, includinga human, said method comprising administering to said animal atherapeutically effective amount of indole-3-propionic acid or a salt orester or protein complex or inorganically bound preparation thereof. Theindole-3-propionic acid or a salt or ester or protein complex orinorganically bound preparation thereof is administered in apharmaceutically acceptable carrier, preferably in a food or beverage.

The present disclosure also provides a method of treating an animalsusceptible to Huntington Disease or other neurodegenerative diseases,or hypertension, stroke or ischemic heart disease, including a human,said method comprising administering to said animal a therapeuticallyeffective amount of indole-3-propionic acid or a salt or ester thereof.The indole-3-propionic acid or a salt or ester or protein complex orinorganically bound preparation thereof is administered in apharmaceutically acceptable carrier, preferably in a food or beverage.

The present disclosure also provides a method for monitoring an animalsuffering from Huntington Disease or other neurodegenerative diseases,or hypertension, stroke or ischemic heart disease such as a human forprogression of said disease, which comprises determining the level orchanges in the level of indole-3-propionic acid in said animal. In apreferred embodiment, the level of indole-3-propionic acid is determinedby examining the animal's blood or plasma, urine or fecal matter.

The present disclosure also provides a method for predicting whether ananimal, including a human, is at risk of progression to symptoms ofHuntington Disease or at risk for or predisposed to otherneurodegenerative diseases, or hypertension, stroke or ischemic heartdisease, comprising analyzing a biological sample from said individualfor a level or changes in the level of indole-3-propionic acid. In apreferred embodiment the biological sample comprises blood or plasma,urine or fecal matter.

In yet another aspect, the present disclosure provides a method forpredicting a response of an animal, including a human, suffering fromHuntington Disease or other neurodegenerative diseases, or hypertension,stroke or ischemic heart disease to a therapeutic agent, comprisingobtaining a biological sample from said individual, analyzing saidsample for the presence of indole-3-propionic acid, and comparing saidanalysis to a known standard and a data base of normal levels and levelsof subjects at risk of or at risk of progression of neurodegenerativediseases, or hypertension, stroke or ischemic heart disease. In apreferred embodiment the biological sample comprises blood or plasmaurine or fecal matter. The biological sample may be analyzed using LC-ECand MS, are employed either in parallel or off-line.

In yet another aspect the present disclosure provides a method fordiagnosing Huntington Disease or other neurodegenerative diseases, orhypertension, stroke or ischemic heart disease in an animal suspected ofsuffering from Huntington Disease or other neurodegenerative diseases,or hypertension, stroke or ischemic heart disease, including a human,comprising obtaining a biological sample from said individual, andanalyzing said biological sample for a level of indole-3-propionic acid.In a preferred embodiment, the biological sample comprises blood orplasma, urine or fecal matter, and the analysis is performed using LC-ECand MS, are employed either in parallel, or off-line.

The present disclosure also provides a method for predicting developmentof Huntington Disease or other neurodegenerative diseases, orhypertension, stroke or ischemic heart disease in an animal, including ahuman, comprising obtaining a biological sample from said individual,and analyzing said biological sample for a level of indole-3-propionicacid. In a preferred embodiment, the biological sample comprises bloodor plasma, urine or fecal matter, and analysis is performed using LC-ECand MS and LCEC/MS, employed either in parallel or off-line.

The present disclosure also provides a method for modification of thegut microflora to increase the level of indigenous indole-3-proprionicacid to protect individuals from developing symptoms of HuntingtonDisease or developing other neurodegenerative diseases, or hypertension,stroke or ischemic heart disease.

The present disclosure also provides a method for protecting an animalfrom effects of or progression of effects from neurodegenerativedisease, hypertension, or ischemic heart disease, or for protectionagainst secondary long term effects of stroke or head injury, comprisingmodifying the gut microflora or microbiome of the animal to increase alevel of indigenous indole-3-propionic acid in the gut.

The present disclosure also provides indole-3-propionic acid as abiomarker or as a therapeutic agent for Huntington Disease or otherneurodegenerative diseases, or hypertension, or ischemic heart diseaseand as a risk factor in the normal population for development of otherneurodegenerative diseases, or hypertension, or ischemic heart disease,or for control of secondary long term effects of stroke or head injury,or a prophylactic for reducing effects of head injury in subjects athigh risk of head injury.

The present disclosure also provides a method for monitoring changes ina healthy state of an individual comprising monitoring changes in thegut microbiome from the foot print of the gut microbiome in the feces ofan individual. In one embodiment, the method comprises the steps ofacquiring a sample of fecal material on toilet paper and immersing thesample in a stabilizing solution; subjecting the sample to survey LCE,MS and LCEC/MS parallel techniques to create a sample profile, andtaking ratios of all compounds in the profile and comparing the ratiosto said individual's prior sample or a data base of samples usingstatistical modeling to determine a category of the individual andchanges in the aggregate composition of the gut microbiome as a resultof intervention.

The present disclosure also provides a home sampling kit for measurementof Indole-3-propionic acid in normal individuals comprising a collectiondevice for preserving Indole-3-propionic acid for testing in urine,blood sample or fecal sample, and a home sampling kit for measurement ofIndole-3-propionic acid in normal individuals, to evaluate effects ofdietary modification or to evaluate effectiveness of dietsupplementation, comprising a collection device for preservingIndole-3-propionic acid for testing in urine, blood sample or fecalsample.

The present disclosure also provides a method for increasing levels ofIndole-3-propionic acid in normal individuals which comprisessupplementing the individual's diet with Indole-3-propionic acid or asalt in ester or protein complex or marginally bound preparationthereof, in a suitable carrier.

In yet another aspect, the present disclosure provides a method fortreating stroke victims against protein damage and post event freeradical damage to brain cells, comprising delivering Indole-3-propionicacids to said stroke victim through injection.

The present disclosure also provides a method of producing purifiedIndole-3-propionic acids in a protein bound matrix through use oforganisms such as brewers yeast operating on purified tryptophan as asubstrate.

The present disclosure also provides a method of assessing the diseaserisk of an individual comprising monitoring changes in the gutmicrobiome from a foot print of the gut microbiome in the feces of saidindividual, and assigning that individual to the lower quartiles of thedistribution of normal values carrying the highest degree of risk.

Finally, the present disclosure provides a method for modifying the riskof an individual developing neurodegenerative disease, hypertension,stroke or ischemic heart diseases or for ameliorating the effects ofhead injury, which comprises administering to said individual acomposition comprising indole-3-propionic acid or a salt or ester orprotein complex or inorganic preparation thereof and a pharmaceuticallyacceptable carrier therefor.

In my earlier U.S. Pat. Nos. 6,194,217 and 6,210,970, the contents ofwhich are incorporated herein, by reference, I disclose methods andsystems for diagnosing, monitoring and categorizing disorders frombiochemical profiles, in particular, the metabolome, using liquidchromatography and electrochemical detection (LC-EC) for profilingelectroactive molecules in bodily fluids such as plasma, urine andcerebral spinal fluid (CSF), nasal swabs, sweat or other body fluid, fordiagnosing disorders in test individuals by categorizing ordifferentiating individuals based on comparisons of biochemicalanalytical data of small molecule inventory against data bases of knownor previously diagnosed cases. While LC-EC studies permit one todifferentiate biochemical differences between patients suffering from HDor other neurodegenerative diseases, or hypertension, stroke or ischemicheart disease and controls, LC-EC studies do not permit one toreproducibly identify specific markers or potential therapies forpatients suffering from HD or neurodegenerative diseases, orhypertension, stroke or ischemic heart disease.

In accordance with the present disclosure, we employed a combination ofseparation and analytical techniques to separate and identify smallmolecule profiles of individual and pooled sample materials to identifyspecific markers, for HD or other neurodegenerative diseases, orhypertension, stroke or ischemic heart disease, and we demonstratedtherapeutic agents for treating individuals suffering from HD or otherneurodegenerative diseases, or hypertension, stroke or ischemic heartdisease. More particularly, we employed a combination of LC-EC and LC-MSarrays in parallel and off-line, to separate and identify the compoundsof the small molecule profiles of individually and pooled samples, toidentify specific markers for HD or other neurodegenerative diseases, orhypertension, stroke or ischemic heart disease, and to monitor anddemonstrate the results of therapeutic intervention. It should be noted,however, that other separation and analytical technologies alsoadvantageously could be used, including, by way of non-limiting example,HPLC, TLC, electrochemical analysis, mass spectroscopy, refractive indexspectroscopy (RI), Ultra-Violet spectroscopy (UV), fluorescent analysis,radiochemical analysis, Near-InfraRed spectroscopy (Near-IR), NuclearMagnetic Resonance spectroscopy (NMR), Light Scattering analysis (LS)and other methods known in the art. Using the above described separationand analytical techniques, we discovered that the gut microbiome productindole propionic acid (IPA) is dramatically reduced in patientssuffering from HD or other neurodegenerative diseases, or hypertension,stroke or ischemic heart disease, and that treating patients sufferingfrom HD or other neurodegenerative diseases, or hypertension, stroke orischemic heart disease with IPA and/or modifying the nature of the gutmicrobiome of an individual suffering from HD or other neurodegenerativediseases, or hypertension, stroke or ischemic heart disease, i.e. toincrease the level of indigenous indole-3-proprionic acid, maysignificantly delay the time before symptoms of the disease occur, aswell as the life span, functionality and quality of life of individualssuffering from HD or other neurodegenerative diseases, or hypertension,stroke or ischemic heart disease. Increasing levels of IPA in the lowertwo quartiles of IPA levels of normal subjects will also potentiallyreduce the risk of these individuals for neurodegenerative diseases, orhypertension, stroke or ischemic heart disease, Increasing IPA inprenatal mothers may also prevent the transmission of HD or tendency torisk of other neurodegenerative diseases, or hypertension, stroke orischemic heart disease to an individual's offspring.

BRIEF DESCRIPTIONS OF THE DRAWINGS

Further features and advantages of the present disclosure are seen fromthe following detailed description, taken in conjunction with theaccompanying drawings, wherein:

FIGS. 1A and 1B show a side-by-side comparison of two off-line LC-ECarray chromatograms showing a single control patient plasma sample postACN precipitation (enclosed) and a single plasma sample from a diagnosedHD patient post ACN precipitation;

FIGS. 2A and 2B show a side-by-side comparison of the same two off-lineLC-EC array chromatograms enlarged in the region 21-32 min;

FIG. 3 is a digital map of data exported from the off-line LC-EC array;

FIG. 4 is a partial least squares determinant analysis showingseparation and grouping of the pre-symptomatic HD at-risk HD, HD sampleswith TFC score 13 and non-HD controls;

FIG. 5 is a partial least squares determinant analysis comparing controlsamples to HD patients with a TFC score of 13;

FIG. 6 is a partial least squares determinant analysis comparing controlsamples and HD patients with TFC scores of 2-6;

FIG. 7 is a partial least squares determinant analysis comparing earlystage HD patient samples with TFC scores of 13 to late stage HD TFCscores of 2-6;

FIGS. 8A and 8B are a comparison of LC-EC array chromatographs of acontrol and HD subject respectively obtained from a 100-min gradiantmethod using the parallel system illustrating the ability of thetechnique to find un expected artifacts such as the un reported use ofthe pain medication Naproxen in survey studies of control vs. diseasesubjects;

FIG. 9 is an example of one peak of particular interest in HD plasmas,9A shows the response of the isolated peak in the parallel LC-EC and 9Bthe corresponding TIC response in the parallel MS;

FIG. 10(A) is an MS/MS spectrum of the peak shown in FIG. 9, and

FIG. 10(B) is a proposed structure for the candidate peaks;

FIG. 11 shows the MS of a 30% acetonitrile fraction of control plasma;

FIG. 12 shows the MS of a 100% acetonitrile fraction of control and HDplasma;

FIG. 13 is a digital map of levels of I3PA in diseased mice compared tolevels of I3PA in wild-type litter mates;

FIG. 14 is a bar graph showing results of analysis of mice feces;

FIG. 15 is a suggested oxidation mechanism for 13PA;

FIG. 16 is a representation of a PK digested fragment;

FIG. 17 are two LC-EC array chromatograms;

FIG. 18 schematically illustrates I3PA combining with ubiquintin as aresult of a “Fenton” reaction;

FIG. 19 are four mass spectra of ubiquintin and I3PA;

FIG. 20 are plots showing isotopic distribution of kynuric acidcovalently and co-ordinately bound to ubiquintin;

FIG. 21 is an MS/MS spectrum of kynuric acid;

FIG. 22 shows the MS/MS spectrum of product assigned as kynuric acid;

FIG. 23 shows the categorical separation of the CAG140 HD mouse modelfrom its wild type littermates based on the foot print ot the gutmicrobiome in feces at 19 days post weaning (left hand panel) and at 3months (right hand panel). The figures as shown are for one of 5 testsof the models using 2/3 training sets and 1/3 validation sets. Thecorrelct classification rate for these models was 90% and 83%respectively. This indicates that the genomic variant imposes a uniquevariationin the aggregate composition of the gut microbiome at a veryyoung age that persists through maturation. IPA was a major variable ofimportance contributing to the separation.

FIG. 24 This PLS-DA model shows a similar separation in the G93A ALSmodel mice from their wild type littermates based on the footprint ofthe gut microbiome and the effect of creatine administration both wildtype and G93A mice on changing the gut microbiome to a different state.This shows that although the gut microbiome is genetically determined itcan be modified by therapeutic intervention. Again in this case I3PA wasa variable of importance in the separation of the gene modified and wildtype mice. However, it was not significantly changed by creatine in thisstudy.

FIGS. 25 A, B and C. these show LCEC chromatograms of fecal sampleacquired on toilet paper into 70% isopropanol and subsequently processedand analyzed. (panel 1 is husband, panel2 is wife). Notable visualdifferences are amplified in FIG. 25C in the region of 75-80 min.

FIG. 26 shows the basic charicteristics of the targeted method for I3PA.the left hand panel shows the progressive decrease in plasma I3PA fromcontrol to Presymptomatic HD to HD subjects using the long gradientLC-EC protocol, which was the initial rationale for developing atargeted method, The middle panel shows the stability of plasma I3PAover a one week period with a plasma sample at room temperature which iscritical for methods aimed at population based screening and theresponse of IPA and linearity of the method in a rapid 8 min. method.Panel three shows the application of a variant of the targeted methodfor urine samples which allowed the definition of two metabolites of IPAand subsequently the ability to monitor IPA levels from urine in bothmouse trials and in human subjects.

FIG. 27 shows the linearity of the targeted method with long gradientmethod chromatograms where I3PA was determined by coulometricintegration of the dominant, leading and following sensor responses ofcoulometric sensors. This allowed the quantitative assay of 13PA inarchived historical studies which had been performed prior to thestructural identification of I3PA and in historical archives of samplesets.

FIG. 28 this shows the PLS-DA separation of husband and wife using 8 and6 fecal samples taken ove a 10-15 day period, processed for LC-ECprofiles as shown in FIG. 25 and analyzed as ratios of all resolvedpeaks. The circled outlier is a sample drawn after five days ofantibiotic therapy post dental surgery. This indicates again theindividual specific character of the gut microbiome reflected in thefoot print of the gut microbiome in feces, ad provide a means ofmonitoring the composition and changes in the gut microbiome.

FIG. 29 shows an example of an ABNOVA box plot of serial plasma 13PAlevels of subjects sampled over time periods of 3 months to 6 years,demonstrating that I3PA levels are an individual specific characteristicand again supporting that I3PA levels are to a large extent geneticallydetermined and consequently low levels as seen in neurodegenerative andcardiovascular disease are a risk factor for these diseases.

FIG. 30 shows a summary of results from a loading study of the 13PAderivative indole propionamide (IPAM). This study led to the realizationthat the correlation between brain plasma and urine allows the trackingof animals in a therapy testing trial can be conducted withoutsacrificing the animals and that population based measurements can beaccomplished with micro samples of either urine or plasma. As with otherstudies it also shows lower levels of IPA in the gene modified vs thewild type littermate mice. The data also indicates that IPAM isconverted rapidly to I3PA in plasma and less rapidly in the gutsuggesting that I3PA delivered to the gut through an appropriate vehicleis a better modality for therapy of supplementation than IPAM.

DETAILED DESCRIPTION Initial Studies

In order to identify potential candidates of interest, we first analyzedprofiles from 200 plasma samples of HD subjects in a drug trial ofcreatine and 35 control subjects using a LC-EC array following theteachings of my U.S. Pat. No. 6,210,970. For the stated initial purposesof the study, the data was exported for compounds in tyrosine,tryptophan and purine pathways that were hypothesized to be affected. Wealso exported the data in digitized form capturing all of theinformation in the profiles. Analysis of this data between HD subjectsand controls revealed a region 50% lower in the HD subjects of highsignificance P=10⁻⁸ in channels 11, and 12 and 78.2 min. From theelectrochemical characteristics, we suspected that this region mightreflect compounds containing an indole moiety.

We then ran in pooled samples spiked pools and standard mixtures of 20indoles varying the chromatography to determine the mobility of theindole mix standard with the qualitatively unidentified peak. Under 5different gradient conditions and with different ion pairing/non-ionpairing and pH mobile phases the unknown compound matched the retentiontime and electrochemical significance of indole propionic acid.

Thereafter we ran over 800 plasma samples from HD and control subjectsand R6/2 and CAG140 HD mouse models and confirmed that thechromatographically identified indole-3-propionic acid (I3PA) wassignificantly lower 42% p=10−6 in both the HD humans and HD mouse. Fromthese studies, and because of the congruence of the mouse model andhuman response we felt that I3PA would be a strong biomarker of HD stateand a useful biomarker for translation of drug trials in mice to humans.

We then initiated source studies of mouse feces from HD and wild typemice which showed lower levels of I3PA in the HD mice confirming thesource of the gut microflora-presumably clostridium sporgenes. Weanalyzed mouse chow and typical human foods and confirmed that levels ofI3PA were too low to account for plasma or brain concentrations.

We analyzed brain samples from HD mouse models and human post mortembrain to confirm that the I3PA did cross the blood-brain-barrier and waslower in both HD mouse brain and human HD brain.

We also created pooled and spiked samples and carried out isolation andconcentration procedures and chromatographic modifications to allowstructural confirmation of the I3PA peak using parallel LC-EC/LC-MS.

Enabled by the development of targeted methods and the comparison oftargeted methods to the survey method values extracted and analyzed bycoulometric integration (FIG. 27), we have also performed studies of IPAlevels in various other diseases, and with various pharm logicalinterventions as set forth below, and recorded results as shown below.

To do this we returned to archived studies and samples of otherconditions in studies with the same methodology dating back to 1992.These were initially undertaken to develop different markers andhypotheses. In these prior studies what we have now confirmed as I3PAhad been identified only as a peak of significance for which we are nowable [1-7] to obtain quantitative values. We also evaluated on-goingstudies to determine the specificity of I3PA as a marker for HD, theeffect of drugs commonly used to treat symptoms of HD and IPA levels inother diseases. The summary below is from 17 different studies in whichwe used standard 2 tail t test statistics to determine the significanceof levels of I3PA between categories and ABNOVA to determine the extentto which I3PA levels are an individual specific characteristic.

Alzheimer's Disease

Study 1. In CSF (from reevaluation of archived chromatograms from U.S.Pat. No. 6,210,970)Control N=66 mean IPA 3.87 ng/mlAD N=60 mean IPA 2.17 ng/ml

P=0.0014

From current work

Study 2. In CSF

Controls N=38 IPA mean 4.05 ng/mlMCI N=39 IPA mean 3.41AD N=40 IPA mean 2.95 ng/mlP AD vs. Control=0.013P MCI vs. control=0.052

Study 3. In Plasma

Controls n=30 mean 189.3 ng/mlAD N=30 mean 154.3

P=0.046 ALS Amyotropic Lateral Sclerosis

Study 4. In Plasma (from re-assay of archived sub aliquots from (7))Controls N=30 mean 192.3 ng/mlALS and Lower Motor Neuron Disease N=30 mean 167.8 ng/ml

P=0.032

Study 5. In CSF (from re-assay of archived sub aliquots from (7))Control N=21 mean 3.25 ng/mlALS N=19 mean 2.24 ng/ml

P=0.054

Study 6 In Plasma (from reevaluation of archived chromatograms from (2))Control N=27 mean 201.2ALS N=23 mean 172.0

P=0.029

From current work

Study 7. In CSF

Control N=30 mean 4.13 ng/mlALS N=30 mean 2.89 ng/ml

P=0.018 Study 8. In Plasma

Control N=56 mean 201.4ALS N=48 mean 172.7

P=0.0072 Parkinson's Disease

Study 9. In CSF (from reevaluation of archived chromatograms fromDATATOP deprynyl study (1))Controls N=47 mean 4.25 ng/mlPD at baseline N=59 mean 3.01 ng/ml

P=0.035

Baseline vs. deprynyl treated subjects p=0.45ABNOVA for serial samples p=6.3*10exp-7Study 10. In Plasma (from reevaluation of archived chromatograms from(3,4))

Controls N=20 Mean 186.9 Un-medicated PD Mean 172.2 P=0.051 Study 11 InPlasma Controls N=30 Mean 196.01

Un medicated PD Mean 167.90

P=0.032 Cardiovascular Disease

From current workIschemic heart subjects pre and post undergoing mental stress testsStudy 12. In plasma

N=20

Baseline mean 175.31 hour post mental stress test mean 161.3 ng/mlBaseline vs. all controls all studies P=0.0016Group baseline vs. post stress P=0.045Group with change normalize to baseline P=0.0014

Stroke:

Study 40 subjects with hemorrhagic and or ischemic stroke. Samples ofCSF, ipsilateral and contralateral jugular plasma. (From reevaluation ofarchived chromatograms of samples from the First Russian MedicalUniversity Stroke Center)

N=40 Study 13. In Plasma

Hemorrhagic stroke N=18 mean 102.1 ng/ml ipsilateral 112.09 ng/ml contralateral ischemic stroke n=22 mean 88.7 ng/ml ipsilateral 83.1 ng/mlcontra lateral p value all plasma vs. other controls p=10exp-6

Study 12. CSF

Hemorrhagic stroke N=18 mean 1.02 ng/mlischemic stroke n=22 mean 0.91 ng/mlp value all CSF vs. other controls p=10exp-8Anti-Depressants and Anti Hypertensives have Little Effect on IPADrug effectsStudy: Depression study of Sertraline (from reevaluation ofchromatograms in (5))Study 15. In plasman=57 baseline I and 4 weeksBaseline mean 192.4 ng/ml4 weeks mean 186.3 ng/mlGroup p value pre and post p=−0.41P value normalized to base line p=0.1ABNOVA test of self-similarity 3 serial samples p=2.6*10 EXP-11Depression study of Escitalopram/citalopramFrom current work

Study 16. In Plasma

N=150 baseline 4 and 8 weeksBaseline mean 205.158 weeks mean 210.09Group pvalue baseline vs. 8 weeks p=0.87Pvalue normalized to baseline p=0.67ABNOVA test of self-similarity 3 serial samples p=9.1*10 EXP-14Hypertension study of AtenololFrom current work

Study 17. In Plasma

N=40 baseline and 8 weeksBaseline mean 169.78 week mean 160.5Group p value baseline vs. 8 weeks p=−0.81Baseline normalized p value p=−0.71Group mean of hypertensive subjects vs. all study controls p=0.0007

We further confirmed that I3PA is a progressive disease marker in HD.Decreasing in pre symptomatic HD vs. Controls and decreasing furtherafter pheno-conversion and development of symptoms. We confirmed thatIPA is statistically significantly reduced in other neurodegenerativediseases although not to the extent in HD and that it is not affected bySSRI and antihypertensive medications used HD and otherneurodegenerative disorder to control concurrent symptoms. It is alsoreduced in ischemic heart disease, stroke and hypertension althoughinterestingly it is not affected by the common treatment forhypertension using atenolol.

Based on these studies, we observed:

(1) lower 13PA is a progressive biomarker of state in HD that ischaracteristic of HD. IPA levels are not affected by depression or bydrugs commonly used to treat depression or hypertension side effectssymptoms of the disease or co morbidities;

(2) I3PA is also lower in other neurodegenerative diseases but not tothe same extent as in HD and lower in in ischemic heart disease andhypertension and stroke;

(3) I3PA is also a progressive biomarker of state in HD mouse models;

(4) I3PA crosses the blood-brain-barrier and may play a role as anantioxidant and in suppressing protein aggregation; and

(5) the source of I3PA is the gut microflora with minimal direct dietaryinput.

These findings suggest the use of I3PA as a biomarker of state andprogression in HD:

-   -   (A) as a biomarker of therapeutic intervention in a drug trials;        and    -   (B) as a biomarker to evaluate/increase the probability that a        drug that works in mice will work in people.

(6) IPA is a compound whose levels are an individual specificcharacteristic shown in FIG. 29 further supporting the geneticdetermination of IPA levels and the indication that such levelsconstitute a modifiable genetic risk of development of certainneurological and cardiovascular disorders.

This suggests that the individual's genome affects/determines theaggregate genome of the individuals gut microbiome. This means for manydiseases with a genetic component (hypertension, autism, ALS with SODmutant gene, HD, Genetic linked PD, genetic linked AD) we should betreating the gut and monitoring the aggregate gut microflora eitherthrough metabolomic profiles in plasma or urine, through measures infeces or through new technologies using MS approaches for bacterial ID.I3PA is an initial discovery using these concepts and approaches thatcan serve both as a therapeutic agent and an agent to reduce the risk ofdisease in individuals with genetically caused low levels of I3PA causedby low production by the aggregate of the commensal gut microbiome.

DETAILED DISCUSSION

Following our initial studies, we then undertook detailed studies asfollows:

Coupling separation and analytical technologies such as LC-EC array andMS technologies together in a parallel LC-EC array-MS system, provides apowerful tool for identifying metabolites in HD. In our investigationsdescribed in this chapter, we used both offline LC-EC array and offlineMS, as well as parallel LC-EC array-MS, to conduct a preliminaryinvestigation of HD versus control plasma samples in order to evaluatethe differences in metabolic signatures between these two groups.

391 plasma samples from 150 subjects enrolled in an ongoing “HDBiomarkers Study” and 40 healthy control subjects were evaluated. Thenumber of samples collected from any one patient varied depending on thetime they were enrolled in the study. Thus, this number ranged from onesample to six, depending on the patient. Samples used for analysis wereselected based on the TFC (total functional capacity) score associatedwith the patient at the time of sample collection. The TFC score is ascale employed by physicians to designate to what extent the individualis affected by the disease. The scale ranges from 1-13 with I being themost severely affected and 13 being the least severely affected.

To create an initial database of compounds that differed between HD andcontrols, all samples were analyzed using gradient LC optimized for ECarray following the teachings of my aforesaid U.S. Pat. No. 6,210,970.Gradient LC-EC analyses were performed using ESA model 582 Pumps (ESABiosciences Inc., Chelmsford, Mass.) and a 16-channel ESA model 5600CoulArray detector. Channels 1-15 used series Coulometric electrodes setin equal increments of 56 mV from 0-840 mV. Channel 16 was set at 870mV. Two 4.6 mm×250 mm series C18 5-μm columns (ESA Biosciences Inc.,Chelmsford, Mass.) were used. The gradient employed was linear from 0%Phase A (0.1 M sodium pentane sulfonic acid with 5% acetic acid) to 100%Phase B (80/10/10 MeOH/isopropanol/acetonitrile with 0.06 M lithiumacetate; 7% acetic acid). The linear gradient was employed to 84minutes, then 100% B was run to 110 minutes. The flow rate was 1 ml/min.

Plasma samples were prepared by a standard method as follows. Plasma(125 μl) was precipitated with 500 μl of ACN/0.4% acetic acid, vortexedfor 30 s, and centrifuged at 21,000×g for 25 min at 4° C. Thesupernatant (500 μl) was centrifugally evaporated and reconstituted to100 μl in mobile phase A; a 50-μl aliquot was injected onto the system.During sample preparation, pools were created from equal volumes of subaliquots of all samples. The assays were run in sequence as follows: aset of combined diagnostic standards (including 80 known compounds), apool of all samples in the study, 8 individual samples from the study,the same diagnostic standards as above, and a global pool. This sequencewas repeated until all samples had been run. Run orders of allindividual samples in the study were randomized. These sequencesminimized possible analytical artifacts during data processing. Poolswere used to assess the precision of the entire data set. Additionally,the pools were used as references for time normalization (peakstretching).

All chromatograms in the study were background corrected to eliminatethe baseline drift inherent in gradient profiles. By controllinganalytical conditions, the location of any particular peak in a16-channel 110-minute chromatogram was held to within +/−5-30 secondsthroughout the study. Background-corrected files were then sequentiallytime normalized against a single pool in the middle of the studysequence. A two-step stretching protocol with a multitude of peaks wasfirst used. First, ESA CEAS 512 software was used to align 15-20 majorpeaks in the chromatogram and interpolate the positions between them.Then, an additional 20-25 smaller peaks present in most samples wereselected from the derivative file and those were realigned, keeping themajor peaks in the same position. Selected peaks were aligned within+/−0.5 seconds and non-selected peaks within +/−1 to 5 seconds over theentire 110-minute assay.

We exported the data in the form of a digital map. Using the completedigital output served two purposes: (1) to capture all analyticalinformation for future data analysis; (2) to avoid possible artifactsintroduced by peak-finding algorithms. The number of variables in thedigital maps depended on the resolution set during the data export. Inthis work the resolution was set at 1.5 sec and the number of datapoints (variables, defined as the signal at a given time on a givenchannel) obtained from one sample, using our current LC-EC arrayapproach, was 66,000. The number of variables in a digital map is notequivalent to the number of analytes, because an individual analyte isrepresented by more than one variable. Depending on the concentration ofan analyte and on its separation across the EC array chromatogram, thenumber of variables characterizing an analyte could be between 10 and100. In the consolidated files of a study, all variables were aligned ina spreadsheet for data analysis with each column representing a singlesample organized by time from channel 1 to 16. Each row in a spreadsheetrepresents the response of a compound (variable) at a specific time andchannel for all samples. This approach avoids artifacts in datareduction and protects against over fitting in the data analysis. Priorto data analysis, rows in the digital maps for which all values werenegative or less than 30 pA (the noise level of an analytical method)for all samples were eliminated.

The data obtained from the digital maps were analyzed using partialleast squares discriminant analysis (PLS-DA). PLS-DA can find individualcomponents that best categorize or explain the variance in a data set.Within a given data set, PLS-DA models can be tested by developing themodel on a subset of the cases and using the variables to test theremaining cases for specificity and selectivity. Thus, SIMCA-P softwarewas used to create three PLS-DA models. Those models included: controlsversus HD samples with TFC score 13; controls versus HD samples with TFCscores 2-6; and HD with TFC 13 versus HD with TFC 2-6. Also generatedwere lists of variables of importance (VIPs). These are the variables(peaks) which best define the separation between the various groups ofdata. Tables of VIPs in all PLS-DAs were generated. Each table gives thedominant EC channel and elution time of the particular VIP.

To verify whether the VIPs suggested by the PLS-DA software were real,visual inspection was done on groups of 16 samples from channel I to 16using the CEAS software. Various groups were compared including controlsamples versus various groupings of HD samples by TFC score. VIPs whichappeared to be most consistent and prominent were noted, as candidatefor identification.

LC-MS analyses were performed using ESA model 582 Pumps (ESA BiosciencesInc., Chelmsford, Mass.) and an ESA model 5600 CoulArray detector,channels 1-12, 0-840 mV in 70 mV increments (ESA Biosciences Inc.,Chelmsford, Mass.) coupled on-line to a QStar quadrupole orthogonaltime-of-flight (Q-o-TOF) mass spectrometer (Sciex/Applied Biosystems,Foster City, Calif.) equipped with an ESI ion source. We sequentiallyused both positive and negative ion scan modes (m/z 100-2000, ionsprayvoltage 4.5-5.5 kV). Metabolite mixtures were separated on a 4.6 mm×250mm (5-μm Shiseido C18) column at a flow rate of 0.8 ml/min. The HPLCeluent was split at a ratio of 9:1 with 90% being directed to theEC-array and 10% being delivered to the MS.

The un-fractionated HD and control plasma samples were diluted between1:10 times in mobile phase A. The dilution was based on the relativeamounts of the compounds of interest and the requirement to 1) performmultiple different runs with varying LC and MS parameters 2) to preservematerial for subsequent MS^(n) studies. Samples were assayed using agradient method. The gradient employed was linear from 0% Phase A (0.2 Mammonium acetate, 5% MeOH) to 80% Phase B (0.2 M ammonium acetate, 80%MeOH). The linear gradient was employed to 100 min, then 100% B was runto 110 min. The flow rate was 0.8 ml/min.

An Information Dependent Acquisition (IDA) MS method was used to monitorthe most intense ion signals in the range m/z 100-1000 and to fragmenteach of these components with the collision energy set to 50 eV and thequadrupole set to low resolution. Using this method, the retention timesof compounds of interest were monitored as they passed through the massspectrometer. Additionally, we compared these retention times to thoseof the peaks detected by the simultaneous EC-array analysis and toobtain initial values for parent masses of the compounds and to obtainthe relevant MS/MS fragmentation.

The parallel LC-EC array-MS method performed on the Q-o-TOF massspectrometer helped us to determine the masses of the metabolites ofinterest which had been selected for MS identification using the offlineLC-EC array method. The purpose of obtaining this preliminary MS datawas to allow us to focus on these particular masses when obtaining exactmasses using a higher resolution mass spectrometer.

Initial qualitative analyses were performed by visual observation of thechromatograms obtained from the parallel LC-EC array-MS system.Chromatograms were overlaid using CoulArray software and compared on all12 channels. First, chromatograms were compared by grouping samples ofsimilar TFC scores and then by cross comparison across a range of TFCscores against control samples. Ten peaks were deemed “of interest”based on the following criteria: a) peaks were present only in HDsamples; b) peaks were present only in control samples; c) peaks changedin intensity as TFC scores changed throughout the course of diseaseprogression; d) peaks had of high enough intensity to suggest that thecomponents would be identifiable by MS. After the peaks of possibleinterest were selected, IDA data was used to determine the masses ofthese peaks.

A small aliquot of each of the samples used for preliminary analysis onthe parallel LC-EC array-MS system was saved for high resolution MS andMS/MS by infusion using a Qh-FT-ICR/12-T Solarix instrument (BrukerCorp., Bremen, Germany).

Because we observed the most prominent differences between control andHD in the samples with the lowest TFC scores, we decided to focus ondetermining the structures of peaks in this group of samples adaptingprotocols we had previously reported (8-10). We obtained three controlsamples and 7 HD samples whose TFC scores ranged from 2-6. These sampleswere prepared by extraction in acidified acetonitrile. Once the HD andcontrol plasmas had been pooled, dried down and concentrated, the poolswere each reconstituted in 200 μl of deionized water. The two pooledplasma samples were then fractionated using solid phase extraction (500mg Diazem C-18 SPE, Diazem Corp. Midland, Mich.). Columns wereequilibrated with 2 ml deionized water, 2 ml acetonitrile and 2 ml 1%acetic acid in deionized water. Each concentrated reconstitutedsupernatant from the two plasma preparations (200 μl) was loaded onto afreshly equilibrated SPE column. For each column, a single 300-μlcollection was made to recover the void fraction and then 1 ml of eachof the following eluants was collected: 10%, 20%, 30%, 40%, and 100%ACN. The fractions were centrifugally evaporated and reconstituted in 20l of 50/50 methanol/water with 0.5% formic acid.

Analysis of IDA data from the parallel LC-EC array-MS system provided alist of the masses of 10 candidate biomarkers. This preliminary MS datathen allowed us to focus on these particular masses while obtainingexact masses using the high resolution SolariX mass spectrometer.

High resolution MS and MS/MS data was obtained using a 12-T Qh/FT-ICRhybrid mass spectrometer (SolariX, Bruker Daltonics) equipped with ananospray source that was operated in the positive mode. Tandem massspectrometry experiments were performed by using the CID activationmode. Samples from the 20%, 30% and 40% ACN fractions were diluted 1:10in 50/50 methanol/water and analyzed. CID fragmentation was performed inthe hexapole. Detection of ions in the SolariX was performed at aresolution of 100,000. The mass assignment accuracy was better than 5ppm.

High resolution MS and MS/MS data was obtained by infusion using anLTQOrbitrap “Discovery” (Thermo-Fisher, San Jose, Calif.) equipped witha with NanoMate TriVersa robot (Advion, Ithaca, N.Y.). Diluted samplesfrom the 30% and 100% ACN fractions were analyzed using nanoelectrosprayin the positive ion mode. Due to the scarcity of sample, nofragmentation experiments were performed. However, it was possible toobtain exact mass values for some compounds of interest. The detectionof intact molecular ions in the Orbitrap was obtained at a resolution of30,000. The accuracy was better than 5 ppm.

Results

Potential biomarkers of HD were identified. Specifically of interestwere compounds that a) were present only in HD samples; b) were presentonly in control samples; c) had changed in intensity as TFC scoresdeclined throughout the course of disease progression; and d) werepresent in sufficient quantity as to be identifiable using MS.

All samples in the study were analyzed according to the protocolsdiscussed above. All 391 plasma samples from 150 subjects enrolled inthe “Biomarkers Study” and 40 healthy control subject plasmas wereprepared by acidified ACN extraction. The samples were vortexed, spunand supernatant removed from the precipitated protein pellet. Theprotein pellet was frozen at −80° C. and the supernatant wascentrifugally evaporated to dryness and reconstituted in buffersappropriate for offline LC-EC array experimentation. FIG. 1 shows aside-by-side comparison of two offline LC-EC array chromatograms showinga single control patient plasma sample post ACN precipitation (A) and asingle plasma sample from a diagnosed HD patient, a single patient postACN precipitation (B) not on drug therapy. Peaks that are either uniqueor significantly different in size are labeled with red arrows. Thefigure was generated directly from the data, using the CoulArraysoftware. Distinct differences between the two are labeled with arrows.

FIG. 2 shows a side-by-side comparison of the same two offline LC-ECarray chromatograms as FIG. 1, however, it is enlarged in the region21-32 min so that differences between the two chromatograms can be seenmore clearly. Peaks that are either unique or significantly different insize are labeled with red arrows. The figure was generated directly fromthe data, using CoulArray software. We then set about to determine thestructures of the compounds which differed between the disease andcontrol plasma samples.

All data obtained using the offline LC-EC array was exported as a“digital map” for analysis. Shown in FIG. 3 is an example of a digitalmap showing variables 45,151-45,171. The digital maps were imported intoMicrosoft Excel, and analyzed using statistical programs as discussedbelow.

Using SIMCA-P software we created partial least squares determinantanalysis (PLS-DA) figures showing the separation of various groups. FIG.4 is a PLS-DA showing separation and grouping of the pre-symptomatic HD,at-risk HD, HD samples with TFC score 13 and non-HD controls. There isseparation visible between the various groups indicating that specificvariables may be involved with categorical separation. FIG. 5 is aPLS-DA comparing control samples (red) to HD patients with a TFC scoreof 13 (black). On the left side of the figure are the peaks (ordeterminants) which are most important in separating the two groups. 5“VIP”s are listed on FIG. 5. After visual inspection of the results fromapproximately 60 samples, the most consistent VIP (that which was seenin at least 80% of the samples examined) is that which appeared onchannel 9 and eluted at 88.75 min.

FIG. 6 is a PLS-DA comparing control samples (red) and all HD patientswith TFC scores of 2-6 (black). Once again, good separation is visible.A list of VIPs is also shown in this figure. Those VIPs highlighted alsoappear to be present in at least 80% of the samples examined, whichminimizes the risk that they are drug metabolite—related peaks orartifacts.

FIG. 7 is a PLS-DA comparing HD patient samples with TFC score 13 HDsamples (red) with TFC scores 2-6 (black). Again, the VIP list isprovided and the compounds highlighted appear to be present in at least80% of the samples, which once again, minimizes the risk that they aredrug metabolite related peaks or artifacts. Once we had obtained outlist of candidate biomarker compounds, it was necessary to translateover to the parallel LC-EC array-MS system.

As before, a parallel LC-EC array-MS separation and detection system(red) was used to analyze all samples (black). A similar systemconsisting of a binary HPLC pump connected to a normal bore C-18 columnfollowed by a 9:1 passive flow splitter that divided the eluant betweenthe EC array and MS detectors was used for data acquisition. The MS flowrate was maintained at 80 μl/min in order to minimize possible ionsuppression effects from both the biological samples and the high saltcontaining EC array buffers and facilitate efficient ion transfer.Additionally, the flow split was important for preserving agreement ofthe retention times between the EC array and the MS chromatograms inorder to allow confident comparison between the results from the twoinstruments and identification of potential HD biomarkers. The delaytimes were adjusted such that a compound would be presented to the ECdetector and the MS detector simultaneously within 1-2 seconds. Thecomponents of interest observed by the two detectors could subsequentlybe further characterized through the combination of high resolution MSmeasurements and CID tandem mass spectrometry (MS/MS).

Shown in FIG. 8 is a comparison of LC-EC array chromatograms obtainedfrom the 100-min gradient method using the parallel system. The toptrace (A) is the chromatogram from one control sample and the bottomtrace (B) is the chromatogram from one HD sample. Arrows point to someof the most prevalent differences between the two samples.

Since the most dramatic changes appeared between the control samples andHD samples with the lowest TFC scores, we decided to focus on theseduring the parallel LCEC array-MS analysis. Using the CoulArraysoftware, we overlaid control and HD sample runs for visual inspection.Shown in FIG. 9 is an example of one peak of particular interest forwhich m/z determination was possible. Shown in panel A is the LCEC arraypeak corresponding to a proposed VIP. In panel B is the correspondingpeak from the IDA method from the QStar MS. The peak shown in FIG. 9 wasdetermined to have [M+H]+m/z 190.09 from the QStar IDA method inpositive mode.

Subsequent high resolution MS and MS/MS of the peak with [M+H]+m/z190.0858 using the LTQ-Orbitrap yielded the fragmentation pattern shownin FIG. 10A. The fragments associated with the loss of H2O and C2H3O2are indicated in the figure with m/z values of 172.0753 and 130.0646respectively. From the fragmentation pattern we were able to assign thestructure of the compound as indole-3-propionic acid (I3PA). Thisstructure is shown in FIG. 10B. The observed mass of I3PA was 189.0780.The calculated mass for I3PA was 189.0790. The error was 5 ppm.

Provided in Table I are elution times and [M+H]+m/z values for each peakof interest taken from the QStar IDA method. These masses are believedto correspond to potential biomarkers.

We were able to see peaks in the range m/z 100-400 on the Orbitrap.Table I shows the m/z values found in mass spectra acquired using theSolariX that were measured for several compounds which differed betweenHD and control pools. Additionally, potential elemental compositions areprovided in table I. FIG. 11 shows the MS of the 30% acetonitrilefraction of control plasma. Some of the most prevalent peaks arecircled.

FIG. 12 shows the MS of the 100% acetonitrile fraction of control (toptrace) and HD (bottom trace) plasma. The quantity of sample wassufficient to obtain MS data for both control and HD from the 100%acetonitrile fraction. Notable differences between the two are circled.In Table II, data from FIG. 11 and FIG. 12 has been organized forsimplification. Several peaks from the 30% acetonitrile fraction fromcontrol plasma as well as the 100% acetonitrile fractions taken fromboth control and HD samples are listed including potential elementalcompositions for each. A mass that correlated with one “biomarkers ofinterest” shown in Table I is highlighted in Table II.

Table III: Several peaks from the Orbitrap that were unique to the 30%ACN fraction from the control plasma pool and the 100% ACN fractionsfrom both HD and control plasma pools are listed.*

* Potential elemental compositions are provided next to each m/z. Noneof these peaks coincided with IDA data from the QStar.

We were able to identify one VIP as indole-3-propionic acid (I3PA).Subsequent re-injection of the I3PA standard at a concentration of 10-5g/ml using the offline LC-EC array method, confirmed that the structureof the VIP was I3PA (shown in FIG. 13). FIG. 13 validates that I3PA is adifferentiator between HD and controls. Shown are relative levels ofI3PA in human HD, control, mouse model HD, and wild-type plasmas.Likewise, in FIG. 14, we have graphed I3pPA levels in feces from R6/2and CAG 140 Mouse N=9 (all P<10²). Results show that HD mouse feces havesignificantly less I3PA than the feces of their wild-type litter mates.Additional studies were performed on I3PA exclusively and will bedescribed below.

Confirmation of I3PA

Indole-3-propionic acid (I3PA) has the molecular weight 189.2. It has aheterocyclic aromatic ring structure with high resonance stability. Itis produced by two types of bacteria Clostridium sporogenes andClostridium cylindrosporum, both of which are found in the smallintestine. Although the full function of I3PA is unknown, I3PA has beendescribed as a potential antioxidant in studies of Alzheimer β-amyloidprotein; in these studies I3PA showed strong levels of neuroprotectionin two examples of oxidative stress. Additional studies in mice andhamsters have shown that I3PA protects neurons from ischemia-inducedneuronal damage by reducing DNA damage and lipid peroxidation. Giventhis information, it was of great interest for us to study both I3PA andits reactive intermediates. Since published reports have shown acorrelation between oxidative damage and HD, determining whether levelsof I3PA were consistently lower in HD patients was of interest. We werealso interested in exploring why levels of I3PA were lower in HD patientsamples.

Plasmas from the mouse model CAG 140 (19 days after birth) were obtainedusing the

following method:

Samples of blood from the CAG 140 mouse model were collected by cardiacpuncture. The blood samples were placed directly into an Eppendorf™tube. Before the blood began to clot, 50 μl was removed from the tubeinto a separately labeled tube. Both samples were kept upright in dryice until all collections were complete. All tubes were centrifuged at8000×g for 20 min to separate red blood cells. Plasma was pipetted fromof the top of the samples and stored at −80° C. All mouse plasma wasthen analyzed using the offline LC-EC array method as before.

Upon completion of plasma analysis, all chromatograms obtained from theabove experiments were exported as digital maps as described above.Values of I3PA were averaged in the HD and control groups and two tailedt-tests were used to compare the levels of I3PA observed in thechromatograms of HD patient plasmas relative to each set of controls.Likewise, in the case of the plasmas obtained from the CAG 140 mousemodel (at 19 days after birth), the levels of I3PA in the diseased micewere compared to the levels of I3PA in the wild-type littermates afteraveraging all values in each group. The results are shown in FIG. 13.The three pairs of bars correspond to the three groupings. The firstpair are the average values of I3PA (ng/ml) in HD and control patientsin the CREST (creatine dose escalation) study (A). The second pair arethe average values of I3PA (ng/ml) in HD and control patients in the“Biomarkers Study” (B). The third pair are the average values of I3PA(ng/ml) in CAG 140 HD and WT collected 19 days after birth (C). Alsoshown on this figure are all p values describing I3PA's level ofsignificance between disease and normal groups. Differences in I3PAlevels are highly significant. In the CREST study, the p value is<10⁻¹⁰. In the Biomarkers Study, the p value is <10-5. In the mousemodel study, the p value is <10⁻⁴. These results show that I3PA levelsare lower in both human HD plasma and mouse HD plasma models as comparedto their non-disease counterparts.

We observed that the differences in the levels of I3PA are statisticallysignificant between diseased and control plasma in both human and mousemodels. While not wishing to be bound by theory, we propose severalhypotheses which might explain the lower levels of I3PA in the diseasesamples.

If human patients/mice with HD have lower plasma levels of 13PA, itsuggests the possibility that the gut bacteria from these subjects arenot producing as much I3PA as in non-disease subjects. Thus, it was ofinterest to determine whether this was the case.

Preparation and extraction protocol for mouse feces:

Feces were directly collected from mice and immediately placed on DryIce after collection. The feces were dried by roto-evaporation andweighed. Dried feces were extracted using acidified acetonitrile. Fiftymg feces were mixed with 1.2 ml of acetonitrile. The samples weresonicated for 30 min and centrifuged at 8000×g. One-ml of supernatantwas removed and evaporated to dryness.

Samples from the procedure above were reconstituted in buffer asdiscussed above. The same LC-EC array method was used for analysis. Alldata was exported as digital maps as discussed above. Values for 13PAlevels were compared and plotted.

Results from the analysis of mouse feces are shown in FIG. 14. In thisfigure there are four pairs of bar graphs. The first pair (A) shows acomparison of the amount of I3PA in mouse feces (ng/g dry weight)collected from 19 day-old CAG 140 HD mice and their WT littermates. Thesecond pair (B) shows a comparison of the amount of 13PA in mouse feces(ng/g dry weight) collected from 120 day-old CAG 140 HD mice and theirWT littermates. The third pair (C) shows a comparison of the amount ofI3PA in mouse feces (ng/g dry weight) collected from 19 day-old R6/2 HDmice and their WT littermates. The fourth pair (D) shows a comparison ofthe amount of I3PA in mouse feces (ng/g dry weight) collected from 90day-old R6/2 HD mice and their WT littermates. Each group had N=9samples.

In all four cases the p values were <10⁻². Thus, we observed lowerlevels of I3PA in the feces of HD mice. The reduced levels could eitherbe attributed to a) lower production of I3PA by bacteria; or b) fewerbacteria. While not wishing to be bound by theory, it has been suggestedthat I3PA undergoes an oxidation mechanism which ends in the formationof kynuric acid. This pathway is shown in FIG. 15.

We also were able to monitor the disappearance of I3PA over the courseof 2 h using a Fenton reaction with the following conditions: 100 μMH₂O₂, 10 μM iron sulfate, 100 μM I3PA. The reaction mixture was kept at4° C. in the dark. Every 30 min, a small aliquot of the reaction mixturewas diluted 1:10 and injected onto the offline LC-EC array system.Although kynuric acid is not EC active, we were able to show thedisappearance of I3PA.

If I3PA is subjected to free radical oxidation in patients with HD(which follows the logic that patients with HD are susceptible to highlevels of oxidative damage), it would suggest that either theintermediate shown in FIG. 15 or kynuric acid itself might become areactive species, capable of forming adducts with proteins. Accordingly,we were interested in determining whether kynuric acid was present in anunbound form in plasma. Thus, five randomly selected untreated HDpatient plasmas were obtained, and were extracted as before the proteinpellet was saved for later use. The supernatant of the plasma wasanalyzed for free kynuric acid using an LC-305 fluorometer (Linear,Alltech Associates, Deerfield, Ill., USA) set at excitation and emissionwavelengths of 360 and 450 nm respectively. Loss of indole fluorescencewas monitored at excitation and emission wavelengths of 285 and 345 nm.No free (unbound) kynuric acid was detected in plasma (LOD at 2%concentration of I3PA). This suggested that if kynuric acid had beenformed, it was likely bound to protein.

Thus, it is seen that I3PA levels are lower at highly statisticallysignificant levels in both HD human and HD mouse model plasma samples.While not wanting to be bound by theory, we believe that lower levels ofI3PA may result from lower production of I3PA by bacteria in the smallintestine. We were able to show that this is the case in two differentmouse model examples (R6/2 and CAG 140) at two different collection timepoints (19 day and 120 day in CAG 140 and 19 day and 90 day in R6/2).However, it is unclear whether the decrease in I3PA production is causedby lower production rates of I3PA by bacteria or the presence of fewerbacteria. Another possibility for decreased levels of I3PA in plasmacould stem from the conversion of I3PA into other products through anoxidation mechanism. Oxidative damage is suggested as a potential causeof neurodegenerative disorders such as HD. Thus, it is possible thatI3PA is converted into other products as a result of elevated levels ofoxidation. Since a primary product of the oxidation of I3PA is kynuricacid, we looked for the presence of kynuric acid in patient plasma.Using a fluorometer set at excitation and emission wavelengths of 360and 450 nm, we looked for kynuric acid. However, none was detected.

Notwithstanding, while no free (unbound) kynuric acid was found inplasma of several randomly selected HD patients, it is believed that thekynuric acid may bind or other reactive intermediate(s) of I3PA toprotein. In order to determine whether this was possible, Fentonreactions with I3PA and human serum albumin (HSA) (in vitro) standardwere designed. Reaction mixtures were prepared as follows: 100 μM H₂O₂,10 μM iron sulfate and 100 μM I3PA were combined with 1 μl of HSA(prepared at a concentration of 10 mg/ml). The reaction was incubated atroom temperature for 1 h.

Two control and two HD plasma samples were selected at random from the“Biomarkers Study.” Plasmas were prepared as per the same protocoldiscussed above. However, for metabolomics experiments the supernate waspipetted off and frozen at −80° C. and we focused on analysis of theprotein pellets. Pellets of HD and control samples were washed with 500μl of H₂O twice to remove acidified acetonitrile. Water (250 μl) wasadded to the HSA-I3PA mixture. A solution of proteinase K (5 μl) whichhad been pre-filtered with a 1OK Centracon™ prep filter to removecontaminants (at a starting concentration of 10 mg/ml) was also added tothe combined mixture. Samples were then placed in a water bath at 57° C.overnight.

An aliquot of the PK solution (1-μl) was added to all protein samplesthat had been subjected to the Fenton reaction with I3PA. Samples werevortexed and placed in a water bath at 57° C. overnight.

All samples which had been in the 57° C. water bath were removed andreextracted with the same protocol discussed above. 125-μl wasprecipitated with 500 μl of ACN/0.4% acetic acid, vortexed for 30 s, andcentrifuged at 21,000×g for 25 min at 4° C. The supernatant (500 μl) wascentrifugally evaporated and reconstituted to 100 μl in mobile phase A;a 50-μl aliquot was injected onto the LC-EC array system. LC-EC arrayanalyses were performed using ESA model 582 Pumps (ESA Biosciences Inc.,Chelmsford, Mass.) and a 16-channel ESA model 5600 CoulArray detector.Channels 1-15 used series coulometric electrodes set in equal incrementsof 56 mV from 0-840 mV. Channel 16 was set at 870 mV. Two 4.6 mm×250 mmseries C18 5-μm columns (ESA Biosciences Inc, Chelmsford, Mass.) wereused. The gradient employed was linear from 0% Phase A (0.1 M sodiumpentane sulfonic acid with 5% acetic acid) to 100% Phase B (80/10/10methanol/isopropanol/acetonitrile with 0.06 M lithium acetate; 7% aceticacid). The linear gradient was employed to 84 min, then 100% B was runto 110 min. The flow rate was 1 ml/min.

Results:

A comparison of the data obtained from the PK digests of in vitrogenerated I3PA oxidation products bound to HSA and the PK digests of HDand control protein pellets indicated similarities. FIG. 16 shows anillustration representing various PK digests. The PK digest of in vitrogenerated HSA reacted with I3PA in a Fenton reaction is shown in (A).(B) shows the PK digestion products of HD protein pellets. (C) shows thePK digestion products of un-reacted HSA. Similarities were observed in(A) and (B) and were not seen in (C) suggesting that an oxidationproduct of I3PA may have bound to the HSA.

Additional evidence suggesting a similarity between PK digests of the invitro created [HSA+I3PA+Fenton reaction] and PK digests of HD proteinpellets is shown in FIG. 17. Here we see two LC-EC array chromatogramsin the 34-41 min range. The blue trace in the top panel represents theHD protein pellet digested with PK. The green trace in the top panelrepresents a control protein pellet digested with PK. The red trace inthe bottom panel represents the products of [HSA+I3PA+Fenton reaction]digested with PK. The black trace in the bottom panel represents HSAdigested with PK. The circled peaks are suggested to have the samestructure in the HD, control and in vitro generated material. Levels ofthe circled compound are significantly higher in HD protein pelletdigests than in controls. We propose that these peaks correlate to anI3PA-related compound bound covalently to an amino acid or peptidefragment containing tyrosine or tryptophan, because these are the onlytwo amino acids that are electrochemically active at the potentialsapplied.

Coulometric integration of the peak gives approximately 2 pmol from the250 μl of plasma, which is estimated to be between 600-1200 pg or2.4-4.8 ng/ml. The position of the peak in the chromatogram suggeststhat it is either bound to a single tyrosine or tryptophan, or to a di-or tri-peptide because its elution is early in the chromatogram relativeto larger peptides such as the endorphins. This experiment suggests thatone mechanism explaining the findings of significantly lower I3PA in HDplasma is due to the reaction of oxidative free radical intermediates ofI3PA and subsequent binding of these intermediates with plasma protein.

The similar peaks found at higher levels in the HD digested proteinpellets suggest that both lower production and increased oxidation ofI3PA could be reasons for lower plasma levels of free I3PA beingobserved in HD.

We then investigated whether we could generate a covalently boundoxidation product of I3PA with a protein. Additionally, determined thestructure of the oxidation product of I3PA and the binding site of theoxidation product on a protein. Two different models were used. Thesewere ubiquitin and angiotensin I. Using MS techniques we hoped toidentify the structure of the oxidation product and binding site.

Free Radical Binding of I3PA Oxidation Product to Ubiquitin Preparationand Method:

A Fenton reaction was performed using the same concentrations ofhydrogen peroxide, iron sulfate and I3PA as discussed above. Onemicroliter of a solution of ubiquitin prepared to a concentration of 10mg/mi was added to the mixture. In addition, a separate tube containingonly the Fenton reaction without ubiquitin was prepared and labeled asthe negative control. The reaction was kept in the dark at 4° C. for 16h.

High resolution MS analysis of the reaction mixtures was performed usinga 12-T Qh/FT-ICR hybrid mass spectrometer (SolariX, Bruker Daltonics)that was equipped with a nanospray source operated in the positive mode.Samples were diluted 1:10 in 50/50 methanol/water, 0.5% formic acid andanalyzed on the SolariX. Detection of ions in the SolariX was obtainedat a resolution of approximately 110,000.

Results:

Analysis of the data obtained on the SolariX indicated likelihood of anon-covalent interaction between an oxidation product of I3PA andubiquitin. An illustration is provided in FIG. 18 demonstrating theattachment of I3PA to ubiquitin as a result of the Fenton reaction.

Shown in FIG. 19 are four mass spectra from the region m/z 794-804.Visible in the bottom spectrum are several peaks. An oxidation productof I3PA is shown bound to ubiquitin in (D). Binding occurs when a Fentonreaction occurs in the presence of I3PA and ubiquitin. In all othercases, no bound material is detected. The circled peak corresponding to[M+11H]′¹+ m/z 799.25584 is found only in the sample containing I3PA,the complete Fenton reaction and ubiquitin. The remaining four spectracorresponding to: ubiquitin alone (A), ubiquitin and I3PA without theFenton reaction (B) and ubiquitin plus I3PA with Fenton reaction withoutiron sulfate (C) do not show the presence of this peak.

Based on a comparison of the isotopic patterns of the peaks in FIG. 19to the theoretical isotopic distributions of both the covalent andnon-covalent adducts of kynuric acid to ubiquitin, it is believed thatthe circled clusters of peaks correspond to two different binding types.The first, circled with a solid line and labeled Coy corresponds to[M+H]⁺ m/z 8779.7598. This peak corresponds to covalently bound kynuricacid. The second, circled with the dotted line and labeled Non-Coycorresponds to [M+H]+m/z 8781.7492. This peak corresponds to residualco-coordinately bound kynuric acid. FIG. 20 shows the region m/z799.0-800.4 magnified with “peaks” indicating the isotopic patterns ofboth the covalent and non-covalent forms of kynuric acid. The isotopicpattern for covalently bound material is outlined in black. The isotopicpattern for co-coordinately bound material is outlined in green. Overlapwas observed because of the small mass difference (2 Da) between thetwo.

Without wishing to be bound by theory, it is believed that the formationof co-coordinately bound kynuric acid reflects the direct conversion ofthe intermediate free radical to kynuric acid during the Fenton reactionbefore it encounters a protein binding site. Because the two forms areso close in mass, the isotopic clusters overlap. A calculation of atheoretical value for ubiquitin ([M+H]+m/z 8560.6287) plus a covalentlybound kynuric acid (C₁₁H₁₁NO₄, exact mass 221.0688) predicts [M+H]m/z8779.7577 for such an adduct. The same calculation with ubiquitin and anon-covalently bound kynuric acid predicts [M+H]⁺ m/z 878 1.6975 forsuch an adduct. The [M+H]+m/z of the first peak was reported as8779.7598. The [M+H]⁺ of the second peak was observed at m/z 8781.7492.This would correspond to a calculated error of −0.24 ppm for thecovalently bound material and −5.8 ppm for the non-covalently boundkynuric acid. In this spectrum, the calculated measurement for theobserved peak assigned to ubiquitin corresponds to a measurement errorof −5.3 ppm. These results were confirmed when the sample was infusedvia nanospray onto the LTQ-Orbitrap. The [M+H]⁺ of the first peak thatwe suggest corresponds to kynuric acid covalently bound to ubiquitin wasobserved at m/z 8779.6766, a measurement error of 9 ppm. The second peakthat we suggest corresponds to kynuric acid non-covalently bound toubiquitin was observed at m/z 8781.6989, a measurement error of −0.16ppm. It is therefore likely that the circled peaks correspond to bothkynuric acid covalently and non-covalently bound to ubiquitin (as thereis only a 2 Da shift between the two). The two additional peaks[M+11H]⁺¹¹ m/z 800.70945 and 801.98019 are likely oxidized forms of thenon-covalently bound kynuric acid/ubiquitin moiety.

In ancillary studies we measured the parent binding constants for I3PAwith whole human plasma, HSA, BSA and ubiquitin using serial additionsof I3PA to determine the number of molar equivalents of binding sitesand mole equivalents of free I3PA. The binding constants (pk) for wholehuman plasma, USA. and BSA are one the order of 10³ or greater than forubiquitin alone. This would suggest that our data for ubiquitin in whichwe saw both covalently and co-coordinately bound kynuric acid, wasrealistic. Increasing the concentration of materials in the Fentonreaction resulted in the over creation of co-coordinately bound kynuricacid, as the I3PA intermediate free radical converted to kynuric acidprior to encountering a protein binding site. Thus, efforts to increasethe yield of covalently bound kynuric acid were prevented by overgeneration of non-covalently bound material. We then decided to attemptthis Fenton reaction with I3PA using angiotensin I as the peptidetarget.

Preparation and Method:

Angiotensin I was obtained from The American Peptide Co in Sunnyvale,Calif., USA. Six tubes were prepared with the following Fenton reactionmixtures: Tubes 1 and 4 contained 100 μM H₂02, 10 μM iron sulfate and100 μM I3PA; Tubes 2 and 5 contained 100 μM H₂02, 100 μM iron sulfateand 100 μM I3PA. Tubes 3 and 6 contained 100 μM H₂O2, 200 M iron sulfateand 100 μM I3PA. Tubes 4, 5, and 6 also contained 1 μl of angiotensin Iprepared to a concentration of 10 mg/ml. A separate tube containing onlythe Fenton reaction without angiotensin I was prepared and labeled asthe negative control. The tubes containing the reaction mixtures werecovered with aluminum wrap so that none of the reagents woulddeteriorate in the ambient light. All reaction mixtures were kept onice. The tubes were left to react for 30 h.

SolariX MS of Angiotensin 1 Plus Fenton Reaction Mixture.

High resolution MS analysis of the reaction mixtures was performed usinga 12-T Qh/FT-ICR hybrid mass spectrometer (SolariX, Bruker Daltonics)that was equipped with a nanospray source operated in the positive mode.Samples were diluted 1:2 in 50/50 methanol/water, 0.5% formic acid (forpositive-ion mode) or 50/50 methanol/water, 0.05% triethylamine (TEA)(VWR Scientific, PA, USA) (for negative-ion mode) and were analyzed onthe SolariX in positive and negative modes. Detection of ions in theSolariX was obtained at a resolution of approximately 110,000. MS/MSfragmentation was performed using CID at 0-10 eV.

Analysis of the reaction tube containing the Fenton reaction productsand I3PA without angiotensin I determined that the primary reactionproduct had [M−H]⁻ m/z 220.0621. This product was only seen in negativemode on the MS. Fragmentation of this compound indicated that the likelystructure corresponded to the anion of kynuric acid [C₁₁H₁₀NO₄]⁻. Shownin FIG. 21 is the MS/MS spectrum of the ion corresponding to [M−H]⁻ m/z220.0621. The fragment at m/z 202.0503 corresponds to the loss of H₂0.The fragment at m/z 176.0710 corresponds to the loss of CO₂. Thefragment at m/z 158.0605 corresponds to the loss of both CO₂ and H₂0.The fragment at m/z 148.0398 corresponds to the loss of C₃H₄O₂. Thecalculated value for the [M−H]⁻ of kynuric acid is m/z 220.0610. Theobserved value was m/z 220.0609. The error was 0.45 ppm. Thus, it islikely that this structure corresponds to kynuric acid.

Analysis of the reaction tubes containing the products from the Fentonreaction, I3PA and angiotensin I determined that fraction 4 containedthe highest quantity of “unique products.” MS/MS of the peak [M+H]⁺ m/z1515.7413, which we theorized corresponded to the covalently boundoxidation product of I3PA (kynuric acid) to angiotensin I was performed.

Table IV provides b- and y-ion fragments of angiotensin I includingobserved values, theoretical values and ppm error. Also shown are allobserved fragments containing covalently bound kynuric acid, likewiseincluding observed and theoretical values as well as the ppm error. FIG.22 shows the MS/MS spectrum of the product which has been assigned askynuric acid (KA) covalently bound to angiotensin I (boxed in blue)represented by the peak with [M+3H]³⁺ m/z 505.9175. Both b- and y-ionsare labeled. Boxed are m/z values of b- and y-fragments containingcovalently bound kynuric acid are boxed in red.

The first covalently bound member of the series was [M+H]⁺ m/z 753.3192.This peak corresponded to [b₄+kynuric acid]. Also present was [M+H⁺ ]m/z866.4036 which corresponded to [bs+kynuric acid]. [M+H]⁺ m/z 1003.4624corresponded to [b₆+kynuric acid]. [M+2H]²⁺ m/z 624.2948 whichcorresponded to [b⁸+kynuric acid]. [M+2H]²⁺ m/z 692.8247 whichcorresponded to [kynuric acid+b₉]. Also observed were [M+3H]³⁺ m/z415.5549 which correspondence to [ys+kynuric acid]; and [M+3H]³⁺ m/z467.5738 which corresponded to [y9+kynuric acid].

Because this series of fragment ions was observed to start at[b₄+kynuric acid], it is believed that the kynuric acid is bound onTyr4. It was to be expected that binding of kynuric acid would haveoccurred on tyrosine, because the aromatic ring on tyrosine is a commonpoint for free radical attack of reactive nitrogen and oxygen species.

Examining plasma data from three separate studies, the “BiomarkersStudy”, the CREST study and a study using the CAG 140 mouse model, wedetermined that plasma levels of J3PA in diseased samples weresignificantly lower than in non-disease controls. The discovery of themarked decrease in plasma I3PA levels led to an investigation ofpossible reasons for this phenomenon. Two hypotheses were proposed.First, because I3PA is produced by bacteria in the small intestine, itwas of interest to determine whether the levels of J3PA in fecal matterof diseased patients was lower than that found in non-disease patients.Although we did not have access to human samples, we were able to useR6/2 and CAG 140 mouse feces which had been collected at two differenttime points. In all four cases, the diseased mice showed significantlylower levels of I3PA in their fecal matter as compared to thenon-diseased wild-type controls. These results suggested that either thebacteria were producing less I3PA in diseased mice, or that there werefewer bacteria. Thus, the presence of the disease genotype clearlyresulted in lower levels of I3PA production and excretion.

A second hypothesis describing why I3PA levels were lower in diseasedpatient plasma stemmed from the theory that oxidative damage, highlyprevalent in neurodegenerative disorders such as HD, caused the I3PA tobe converted into an oxidation product, lowering levels of I3PA andperhaps creating a protein-bound oxidation product of 13PA. A potentialoxidation product of an in vitro reaction “mimicking” oxidative damagein the body was considered. We then sought to determine whether anykynuric acid was present in UD plasma. Although kynuric acid is not anelectrochemically active structure, using a fluorometer, we investigatedwhether any kynuric acid was present in HD plasma. None was detected. Asecond possibility was that the kynuric acid had become bound to aplasma protein. In order to determine whether this type of reactioncould occur in vivo, an in vitro reaction was simulated to mimic freeradical oxidation of I3PA in the presence of angiotensin I andubiquitin. Using MS we were able to determine that kynuric acid boundboth covalently and co-coordinately to ubiquitin as well as covalentlyto angiotensin I. We identified the covalent binding site of kynuricacid on angiotensin I to be Tyr4.

Lastly, we compared PK digests of HD and control protein pellets to invitro generated covalently bound oxidation products of I3PA to USA. Weprepared Fenton reaction solutions containing I3PA and USA. These weredigested with PK and compared to PK digests of UD and control proteinpellets using the offline LCEC array method. Several similarities weredetected, suggesting the possibility that an oxidation product of I3PA(possibly kynuric acid) was indeed bound to the HD protein pellets,possibly somewhere on HSA.

Various changes may be made in the above disclosure without departingfrom the spirit and scope thereof. Indeed, my investigation of ANOVA andABNOVA analysis of the 612 subjects for whom we had serial samples withthe null hypothesis that variance of the data was due to variance withindividuals gave a p value of less than 10 exp-16 indicating stronglythat in the absence of intervention IPA levels are an individualspecific characteristic.

The information indicates that low levels of IPA are associated withfour major neurological diseases and with ischemic heart failure andstress related events in heart failure subjects.

Moreover, as discussed below low levels of IPA are an individualcharacteristic determined in part by the effect of an individual'sgenome on the aggregate genome of the gut microbiome and thus are agenetically determined risk factor in the development of disease. Thisinsight implies that population wide screening for IPA using techniquesbased on the rapid methods described and providing a means of increasingIPA levels through direct supplementation or modification of the gutmicrobiome through use of agents such as Froximum or dietarymanipulation will provide a population wide decrease in degenerative orlate onset diseases. Particularly those in which oxidative stress,related mitochondrial dysfunction and protein damage and aggregation arean eventual effect cumulative insult.

Methodology also has been developed for direct monitoring of theaggregate composition of the gut microbiome using fecal material.

In mouse trials sample acquisition is relatively simple involving onlycollection of fecal pellets and processing them with dry weight as anormalizer of values to obtain a metabolomic pattern reflecting theaggregate “footprint” of the gut microflora. Interpretation ofdifferences is made simple because of the consistency of diet.

Measurement of such patterns in wild type and gene modified mice asshown below indicate that even at a very early age the footprint of thegut microflora is strongly influenced by the genome of the animalitself. Indeed we have determined that the microbiome foot printuniquely separates wild type mice from their gene positive littermatesat weaning well before any onset of symptoms, or any measures ofhistopathology. An example is shown in FIG. 23 for young and old CAG 140HD mouse models. Two of the variables of importance with the highestvalues in discriminating these gene positive and wild type mice fromfeces are IPA and the ratio of IPA to Indole lactic acid, with lower IPAand higher IPA/indole lactic acid in the gene positive mice.

Thus the genome that eventually determines the onset of disease alsodetermines the aggregate makeup of the gut microbiome in an individual.

A second example incorporating the use of gut microflora modification isshown in FIG. 24. Administration of the compound Froximum (a folk remedycomprised of volcanic ash) changes the metabolomic profile of the G93amouse brain, spinal cord and blood. However, this compound by its natureas an inorganic ash cannot cross the gut to plasma or the plasma tobrain. The effect is on the aggregate gut microbiome which is thensubsequently reflected in beneficial changes in other organs. As shownin FIG. 24 the separation of treated and untreated ALS model G93A fromthe changes in the microbiome footprint are sufficient to uniquelydiscriminate treated and un treated mice-in this case moving the ALSmouse model closer to the state of the wild type littermates. Again IPAwas a strong variable of importance in this separation and lower in thegene positive mouse and elevated in both the treated gene positive andwild type littermates. The micro biome footprint of the G93a, CAG 140and their respective wild type littermates were also significantlydifferent from each other.

This indicates that: first a therapeutic compound for CNS disorders doesnot necessarily have to cross the blood brain barrier to have a profoundeffect on the network of genomic proteomic metabolomic and gutmicrobiome interactions that are beneficial to health and or deleteriousto health; second that a compound that my cross the Blood brain barriermay also have a secondary effect on the gut microbiome that can beeither beneficial or deleterious.

First implication is that strategies to prevent or delay the onset ofsymptoms of CNS diseases with a genetic component or predisposition suchas Huntington's Alzheimer's, Parkinson's or ALS should includeapproaches to the modification of the aggregate makeup of the gutmicrobiome, and that these approaches should be undertaken at a veryearly stage prior to the onset of any potential systems. Essentially theaggregate composition of the gut microbiome like the individuals genomeitself is a risk factor in neurodegenerative disease. However thisindividual aggregate gut microbiome genome can be more readily modifiedto a more beneficial state than that of the individual themselves.

Second implication is that in any trial of a potential therapeutic thefoot print of the gut microbiome should be monitored. Changes introducedby a therapeutic agent could be beneficial or harmful and such changescan be compared against a data base for compounds in either category.Significant changes in the individuals gut microbiome which is stablewithout significant intervention can also be monitored

To implement this approach we developed a protocol that could be appliedto both monitoring without necessity of a clinical visit in a drug trailand to population based screening if indicated

In humans monitoring of the gut microbiome footprint is more complexbecause of issues related to sample acquisition and interpretationbecause of dietary variation. The first issue has been addressed bysimply taking a piece of used toilet paper after a bowel movement andplacing it in a 50 ml tube containing 70% isopropanol (rubbing alcohol acommon use material) which can be stored refrigerated and subsequentlyshipped to a laboratory.

Direct analysis of the supernate or supernate concentrates from the tubeyields patterns as shown in (FIGS. 25A, B, and C) from baseline samplesin the short proof of principle study of the time stability of theindividual gut microbiome in a husband and wife described below. Thetechnical innovations are in normalizing the data and in development ofa statistical approach to eliminating dietary variations.

Initial normalization on concentrated aliquots is performed bycentrifugal evaporation in tared tubes and diluting with running bufferto equivalent concentrations in g/ml.

Secondary Normalization for data analysis and profile matching is doneby quantitatively analyzing the all resolved peaks against a pooledsample and taking the ratio of each peak to all others. i.e. in thisexample with 785 resolved peaks the number of ratios and values foranalysis is 308,505.

Dietary variations are expected to have inconsistent ratios whereascompounds that are direct precursors and products of microbialmetabolism are expected to be relatively consistent assuming nosignificant change in the aggregate microbiome.

In classifying individuals from serial samples using all ratios in PCAor supervised PLS-DA models the ratios of compounds that reflectaggregate gut microbiome activity would be expected to be the dominantvariables of importance discriminating one individual from another, andthe most significant variables defining a change from individualtemporal similarity reflecting a change in the gut microbiome.

An example of this approach is shown in FIG. 24. Fecal material ontoilet paper was acquired from a husband and wife sharing similar dietsand medications over a period of 15 days by placing used toilet paperinto a 50 ml tube containing 70% isopropanol. One sample was collectedfrom the husband following 5 days of post dental reconstructionantibiotic therapy at day 20 (outlier in blue). Samples were maintainedat 4 C until assay. Patterns were developed and ratios obtained asdescribed above. The data was then analyzed by PLS-DA modeling. Thevariables with the highest Variable of importance values (greater than2.5) were all compound ratios. One out modeling showed a consistency ofvariables of importance for the separation the principle known compoundratios were IPA/indolelactic acid, IPA/cresol, cresol/tyrosine,tryptophan/indoleacetic acid and tryptophan/IPA.

This indicates that even in the same environment the aggregate gutmicrobiome of two individuals is different. Supporting the influence ofthe individual's genetic makeup on the structure of the microbiome. Itis an open question as to whether the metabolic foot print of themicrobiome will be a better discriminator of individuals than theaggregate gene mapping of the microbiome.

FIG. 26 illustrates the first criterion for selecting compounds fortargeted methods is that is a progressive biomarkers-as shown by thetrend from C to PMHD to HD in the left hand panel for IPA. A practicalcriterion is stability. In the second panel stability of IPA in plasmashows only 5% degradation after 7 days at room temperature. Methoddevelopment then involves integrating simplest preparative andinstrument protocols for speed and minimum sample size andinterferences. A preparative protocol using a simple 3:1 addition ofmethanol to plasma centrifuging and injecting supernate was matched to amobile phase, column and detector settings allowing sensitivity to 2ng/ml, linearity across the range and analysis with no currentlydetermined interferences. The method was also adapted to brain feces andurine for animal trials to demonstrate the congruence of the biomarkerin humans and HD mouse models as a desirable condition for using mousemodels in therapeutic trials. The third panel illustrates theapplication of the method to mouse urine in a dose loading study of IPAMshowing two metabolites in dosed animals (green) and the same twometabolites in un dosed mice (blue) and in human urine (red). The dosedanimal urine provided sufficient material for isolation and MSdetermination as probable glucuronide type Phase II metabolite compoundswith M/Z of 480.14 and 482.15 respectively

FIG. 27A provides a comparison of plasma sub aliquots using the targetedIPA method vs. values derived by integrating the dominant leading andfollowing peaks in the chromatograms from the long gradient surveymethod. The duplicate pair 11% rsd between the methods is trivial withrespect to the biological variability of 100-125% rsd. This studyallowed the derivation of accurate values from archived chromatogramsfrom the last 21 years in which the IPA was present as a signal that hadnot been structurally identified or included in the mixed calibrationstandard used for all assays at that time.

Referring again to FIG. 23, the left hand panel shows one of a series of(two out) tests of the PLS-DA model for assessing the degree to whichthe foot print of the gut microbiome reflected in the dry weightnormalized coordinately bound LCECA patterns of feces allowscategorization of young 19 day littermate WT and GP CAG 140 mice.Training sets of 8 and validation sets of 2 are sequentially evaluatedfor all samples. In the example shown both GP and one WT were correctlyclassified. A similar model for old 90 day WT and GP CAG140 mice isshown in the left hand panel where both were correctly classified.Overall for the young an old categories CCR is 0.83 and 0.81respectively. That suggests that we can currently categorize geneticstatus of a mouse by its microbiome foot print about 80% of the timeeven prior to any symptoms.

FIG. 24 illustrates fecal patterns of the gut microbiome footprint showcomplete categorical separation for the ALS mouse model G93A (ALS inred) and wild type littermates (WT in black). Froximum treated WT andTRTWT and G93A TRTALS in blue and green move to a different space inwhich they are more congruent with each other. Similar althoughcategorically weaker separations are seen in the metabolic profiles ofpost mortem brain and spinal cord.

FIG. 25A illustrates a pattern of gut microbiome footprint fromisopropanol extract of approximately equal quantities fecal material ontoilet paper at low amplification of 10 ua full scale for twoindividuals (1 and 2)

FIG. 25B shows a pattern of gut microbiome footprint from isopropanolextract of approximately equal quantities fecal material on toilet paperat medium amplification of 1 ua full scale for two individuals (1 and 2)

FIG. 25C shows a pattern of gut microbiome footprint from isopropanolextract of approximately equal quantities of fecal material on toiletpaper at low amplification of 500 ua full scale for two individuals (1and 2) showing regions of significant differences.

FIG. 28 shows a PLS-DA 3 component model of gut microbiome footprintsignatures derived from toilet paper fecal samples placed into 35 ml of70% isopropanol 50 ml tubes and processed for LCECA profiles. 6 samplesover a 15 day period from wife (red) and 7 samples over a 15 day periodfrom husband (black) and one taken at 20 days after use of an antibioticpost dental surgery shown in blue.

FIG. 29 shows an ABNOVA box plot of individuals with IPA levelsdetermined on serial samples over times of 6 months to 5 years. The Pvalue for the null hypothesis (that the scatter in IPA values is withinindividuals and not due to individual specific differences) is2.1*10exp-16 which is a highly significant indication that I3PA is anindividual specific characteristic over time

FIG. 30 shows the results of a loading study of the I3PA derivativeindole propionamide (IPAM) in the R6/2 HD mouse model from which wederived and developed methods for monitoring IPA levels in plasma andbrain from urinary metabolites of IPA.

A cohort of R6/2 HD mice were dosed daily for 3 weeks intra peritonealwith 200 ug of the IPA derivative amide indole propionamide (IPAM) andcompared with undosed R6/2 and their wild type littermates. Feces andurine were collected at the time of sacrifice and blood and brain aftersacrifice. The data indicates:

1. That the brain and plasma levels correlate with urinary levels andthus animals can be tracked in a drug trial without sacrifice.2. That IPAM is converted rapidly in the blood to IPA but less rapidlyin the gut, resulting in levels in brain that correlate with plasma IPAlevels suggesting that direct administration of IPA would be a betteralternative than use of the derivative.3. The R6/2 levels of IPA in brain and plasma are lower than in wildtype mice. In this study although feces levels were lower the decreasewas not significant.

In yet another aspect of the disclosure we provide a method forpreparation of purified indole therapies. Indoles as a class are subjectto degradation and contamination such as the problem encountered withpreparations of tryptophan that were related to development basaleosinophilia. Nominally pure commercial sources of indoles whenevaluated using ultra-sensitive LCECA techniques show traces of othercompounds from the ug/mg to (pg/mg) levels (part per billion to sub partper trillion). These are potentially harmful. Pharmaceutical grade andsupplemental tryptophan has now been brought to levels high purity thatcan be verified by LCECA. To take advantage of this we have developed aprotocol for creating high concentrations of IPA using brewers yeastwhich also produces IPA with relatively good efficiency operating on asubstrate of glucose and tryptophan. Brewers yeast as such is a commonsupplement and present as an extract in typical research mouse feed.Production of IPA in this matrix provides a highly purified IPA in averifiably and long accepted matrix. As an example a preparation of 1 gof brewers yeast, 500 mg of glucose and 50 mg of tryptophan allowed toincubate to completion at room temperature (90-120 min) in 35 ml ofdistilled water yields ca. 3 mg of IPA. Passing the supernate through a1 OK MW filter indicates that 75-80% of the IPA is coordinately bound tobrewers yeast protein. The bound material is extractable in organicsolvents but does not release significantly in HCl at concentrationsfound in the stomach. Protein bound IPA as a means of dosing in eitheranimal or human trials allows the IPA to get to the Gut prior to beingreleased from the protein and consequently provide both increased levelsin plasma and potentiate changes in the aggregate gut microbiome. Theprocess is inherently capable of scaling to any desired level.

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1. A method for modifying the risk of an individual developingneurodegenerative disease, hypertension, stroke or ischemic heartdiseases or for ameliorating the effects of head injury, which comprisesadministering to said individual a composition which comprisesindole-3-propionic acid, indole lactic acid or a mixture ofindole-3-propionic acid and indole lactic acid or a salt or ester orprotein complex or inorganically bound preparation thereof and apharmaceutically acceptable carrier therefor.
 2. The method of claim 1,including the step of monitoring the efficacy of said administration bymonitoring changes in the gut microbiome from a foot print of the gutmicrobiome in the blood, urine or feces of said individual.